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CourseClub NET Udacity Data Scientist v1

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[CourseClub.NET] Udacity - Data Scientist v1.0.0

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Total Size

7.9 GB

Total Files

8307

Hash

74374C93EF533440A22171C1ECCE73D5D060BFAD

/Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/

01. Welcome-SaSzn718doY.en.vtt

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01. Welcome-SaSzn718doY.mp4

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01. Welcome-SaSzn718doY.pt-BR.vtt

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01. Welcome.html

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02. Creating Customer Segmentation Arvato Project-VCChvqoK6Go.en.vtt

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02. Creating Customer Segmentation Arvato Project-VCChvqoK6Go.mp4

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02. Creating Customer Segmentation Arvato Project-VCChvqoK6Go.pt-BR.vtt

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02. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.en.vtt

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02. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.mp4

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02. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.pt-BR.vtt

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02. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.zh-CN.vtt

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02. Kaggle Project Final For Classroom-Ssttix340C8.en.vtt

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02. Kaggle Project Final For Classroom-Ssttix340C8.mp4

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02. Kaggle Project Final For Classroom-Ssttix340C8.pt-BR.vtt

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02. Projects-1-E_ZYovKeI.en.vtt

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02. Projects-1-E_ZYovKeI.mp4

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02. Projects-1-E_ZYovKeI.pt-BR.vtt

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02. Projects.html

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03. Program Structure Schedule.html

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04. Learning Plan - First Two Weeks.html

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05. Pre-assessment.html

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06. Extracurriculars.html

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07. Meet The Instructors-ndyjFUF2e9Q.en.vtt

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07. Meet The Instructors-ndyjFUF2e9Q.mp4

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07. Meet The Instructors-ndyjFUF2e9Q.pt-BR.vtt

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07. Meet Your Instructors.html

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08. Getting Help - Community Support.html

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09. How to Succeed.html

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09. L1 06 How To Succeed REPLACEMENT-JRnZOZR97QQ.en.vtt

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09. L1 06 How To Succeed REPLACEMENT-JRnZOZR97QQ.mp4

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10. Careers Team Content.html

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11. Meet the Careers Team-cuKecPpZ7PM.en.vtt

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11. Meet the Careers Team-cuKecPpZ7PM.mp4

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11. Meet the Careers Team-cuKecPpZ7PM.pt-BR.vtt

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11. Meet the Careers Team.html

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12. Access Your Career Portal.html

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13. Your Udacity Professional Profile.html

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14. Parting Words Of Encouragement-sFF_WOnpsXM.en.vtt

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14. Parting Words Of Encouragement-sFF_WOnpsXM.mp4

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14. Parting Words Of Encouragement-sFF_WOnpsXM.pt-BR.vtt

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14. Words of Encouragement.html

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index.html

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/img/

get-hired-with-the-udacity-career-portal.gif

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udacitylogo-copy.png

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/Part 01-Module 02-Lesson 01_Setting Up Your Computer/

01. Intro.html

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01. Introduction-Yg0gBpTzkMo.en.vtt

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01. Introduction-Yg0gBpTzkMo.mp4

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01. Introduction-Yg0gBpTzkMo.pt-BR.vtt

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02. Python Installation-2_P05aYChqQ.ar.vtt

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02. Python Installation-2_P05aYChqQ.en.vtt

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02. Python Installation-2_P05aYChqQ.mp4

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02. Python Installation-2_P05aYChqQ.pt-BR.vtt

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02. Python Installation-2_P05aYChqQ.zh-CN.vtt

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02. Python Installation.html

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03. [For Windows] Configuring Git Bash to Run Python.html

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04. What is Anaconda.html

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05. Installing Anaconda.html

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06. Managing packages.html

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07. On Python versions at Udacity.html

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08. Running A Python Script-vMKemwCderg.ar.vtt

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08. Running A Python Script-vMKemwCderg.en.vtt

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08. Running A Python Script-vMKemwCderg.mp4

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08. Running A Python Script-vMKemwCderg.pt-BR.vtt

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08. Running A Python Script-vMKemwCderg.zh-CN.vtt

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08. Running a Python Script.html

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09. Programming Environment Setup-EKxDnCK0NAk.ar.vtt

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09. Programming Environment Setup-EKxDnCK0NAk.en.vtt

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09. Programming Environment Setup-EKxDnCK0NAk.mp4

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09. Programming Environment Setup-EKxDnCK0NAk.pt-BR.vtt

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09. Programming Environment Setup-EKxDnCK0NAk.zh-CN.vtt

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09. Programming Environment Setup.html

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10. Jupyter-qiYDWFLyXvg.ar.vtt

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10. Jupyter-qiYDWFLyXvg.en.vtt

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10. Jupyter-qiYDWFLyXvg.mp4

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10. Jupyter-qiYDWFLyXvg.pt-BR.vtt

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10. Jupyter-qiYDWFLyXvg.zh-CN.vtt

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10. What are Jupyter notebooks.html

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11. Installing Jupyter Notebook.html

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12. Launching the notebook server.html

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13. Notebook interface.html

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14. Markdown cells.html

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15. Code cells.html

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16. Keyboard shortcuts.html

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17. Magic keywords.html

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18. Converting notebooks.html

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19. Creating a slideshow.html

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20. L2 02 Outro REPLACEMENT-W-6Se0G_FVE.en.vtt

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20. L2 02 Outro REPLACEMENT-W-6Se0G_FVE.mp4

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20. Outro.html

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index.html

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/img/

conda-create-env.png

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conda-environments.png

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conda-install.png

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conda-search.png

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conda-tab.png

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magic-matplotlib.png

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magic-pdb.png

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magic-timeit.png

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magic-timeit2.png

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nbconvert-example.png

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new-notebook.png

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notebook-components.png

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notebook-download.png

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notebook-json.png

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notebook-server.png

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notebook-shutdown.png

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server-shutdown.png

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slides-cell-toolbar-menu.png

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slides-choose-slide-type.png

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step1-cd.png

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step2-pwd.png

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step3-path.png

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step4-alias.png

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step5-source.png

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step6-testrun.png

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/media/

Markdown+cells.mp4

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command+palette.mp4

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conda_default_install.mp4

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conda_install.mp4

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notebook+interface.mp4

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/Part 01-Module 03-Lesson 01_What Is Ahead/

01. What Do Data Scientists Do-sN2DbIJUZmw.en.vtt

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01. What Do Data Scientists Do-sN2DbIJUZmw.mp4

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01. What Do Data Scientists Do-sN2DbIJUZmw.pt-BR.vtt

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01. What do Data Scientists Do.html

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02. Adam from IBM-NjjtY5UHyac.en.vtt

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02. Adam from IBM-NjjtY5UHyac.mp4

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02. Adam from IBM-NjjtY5UHyac.pt-BR.vtt

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02. Interview Adam [IBM].html

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03. Interview Rachel [Kaggle].html

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03. Rachel from Kaggle-uVsYYzxbyIg.en.vtt

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03. Rachel from Kaggle-uVsYYzxbyIg.mp4

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03. Rachel from Kaggle-uVsYYzxbyIg.pt-BR.vtt

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04. Interview Robert [Figure8].html

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04. What'S Ahead Figure 8 Fix-SE4TQnOwmBI.en.vtt

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04. What'S Ahead Figure 8 Fix-SE4TQnOwmBI.mp4

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04. What'S Ahead Figure 8 Fix-SE4TQnOwmBI.pt-BR.vtt

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05. Outro-xj70jX9Moxs.en.vtt

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05. Outro-xj70jX9Moxs.mp4

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05. Outro-xj70jX9Moxs.pt-BR.vtt

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05. Outro.html

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index.html

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/Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/

01. Introduction-LcX-s-ujp7U.en.vtt

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01. Introduction-LcX-s-ujp7U.mp4

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01. Introduction-LcX-s-ujp7U.pt-BR.vtt

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01. Introduction.html

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02. History - A Statistician's Perspective.html

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02. History - Statisticians Perspective-zNNouqLGF9E.en.vtt

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02. History - Statisticians Perspective-zNNouqLGF9E.mp4

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02. History - Statisticians Perspective-zNNouqLGF9E.pt-BR.vtt

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03. A Little More History - A Computer Scientist's Perspective-sVT9nX6HTyU.en.vtt

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03. A Little More History - A Computer Scientist's Perspective-sVT9nX6HTyU.mp4

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03. A Little More History - A Computer Scientist's Perspective-sVT9nX6HTyU.pt-BR.vtt

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03. History - A Computer Scientist's Perspective.html

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04. Types Of Machine Learning - Supervised-Jn3xugBvs2U.en.vtt

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04. Types Of Machine Learning - Supervised-Jn3xugBvs2U.mp4

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04. Types Of Machine Learning - Supervised-Jn3xugBvs2U.pt-BR.vtt

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04. Types of Machine Learning - Supervised.html

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05. Types of Machine Learning - Unsupervised Reinforcement-yg4A99NMzAQ.en.vtt

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05. Types of Machine Learning - Unsupervised Reinforcement-yg4A99NMzAQ.mp4

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05. Types of Machine Learning - Unsupervised Reinforcement-yg4A99NMzAQ.pt-BR.vtt

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05. Types of Machine Learning - Unsupervised Reinforcement.html

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06. Deep Learning And Neural Networks-4rKw3ekE5Wk.en.vtt

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06. Deep Learning And Neural Networks-4rKw3ekE5Wk.mp4

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06. Deep Learning And Neural Networks-4rKw3ekE5Wk.pt-BR.vtt

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06. Deep Learning.html

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07. Scikit Learn-kxvmG8ZsOVg.en.vtt

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07. Scikit Learn-kxvmG8ZsOVg.mp4

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07. Scikit Learn-kxvmG8ZsOVg.pt-BR.vtt

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07. Scikit Learn.html

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08. Ethics in ML-fNcTTXR8T08.en.vtt

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08. Ethics in ML-fNcTTXR8T08.mp4

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08. Ethics in ML-fNcTTXR8T08.pt-BR.vtt

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08. Ethics in Machine Learning.html

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09. What's Ahead-2Hxy2Jlu8nk.en.vtt

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09. What's Ahead-2Hxy2Jlu8nk.mp4

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09. What's Ahead-2Hxy2Jlu8nk.pt-BR.vtt

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09. What's Ahead.html

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10. Text Recap.html

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index.html

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/img/

screen-shot-2018-05-29-at-4.06.53-pm.png

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screen-shot-2018-05-29-at-4.19.03-pm.png

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/Part 02-Module 01-Lesson 02_Linear Regression/

01. Intro.html

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01. Welcome To Linear Regression-zxZkTkM34BY.en.vtt

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01. Welcome To Linear Regression-zxZkTkM34BY.mp4

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01. Welcome To Linear Regression-zxZkTkM34BY.pt-BR.vtt

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02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.en.vtt

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02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.mp4

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02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.pt-BR.vtt

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02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.zh-CN.vtt

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02. Quiz Housing Prices.html

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03. Solution Housing Prices-uhdTulw9-Nc.en.vtt

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03. Solution Housing Prices-uhdTulw9-Nc.mp4

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03. Solution Housing Prices-uhdTulw9-Nc.pt-BR.vtt

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03. Solution Housing Prices.html

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04. Fitting A Line-gkdoknEEcaI.en.vtt

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04. Fitting A Line-gkdoknEEcaI.mp4

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04. Fitting A Line-gkdoknEEcaI.pt-BR.vtt

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04. Fitting a Line Through Data.html

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05. Moving A Line-8EIHFyL2Log.en.vtt

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05. Moving A Line-8EIHFyL2Log.mp4

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05. Moving A Line-8EIHFyL2Log.pt-BR.vtt

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05. Moving a Line.html

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06. Absolute Trick-DJWjBAqSkZw.en.vtt

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06. Absolute Trick-DJWjBAqSkZw.mp4

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06. Absolute Trick-DJWjBAqSkZw.pt-BR.vtt

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06. Absolute Trick.html

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07. Square Trick-AGZEq-yQgRM.en.vtt

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07. Square Trick-AGZEq-yQgRM.mp4

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07. Square Trick-AGZEq-yQgRM.pt-BR.vtt

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07. Square Trick.html

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08. Quiz Absolute and Square Trick.html

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09. Gradient Descent-4s4x9h6AN5Y.en.vtt

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09. Gradient Descent-4s4x9h6AN5Y.mp4

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09. Gradient Descent-4s4x9h6AN5Y.pt-BR.vtt

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09. Gradient Descent.html

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10. Mean Absolute Error-vLKiY0Ehors.en.vtt

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10. Mean Absolute Error-vLKiY0Ehors.mp4

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10. Mean Absolute Error-vLKiY0Ehors.pt-BR.vtt

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10. Mean Absolute Error.html

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11. Mean Squared Error-MRyxmZDngI4.en.vtt

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11. Mean Squared Error-MRyxmZDngI4.mp4

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11. Mean Squared Error-MRyxmZDngI4.pt-BR.vtt

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11. Mean Squared Error.html

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12. Quiz Mean Absolute Squared Errors.html

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13. Minimizing Error Functions-RbT2TXN_6tY.en.vtt

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13. Minimizing Error Functions-RbT2TXN_6tY.mp4

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13. Minimizing Error Functions-RbT2TXN_6tY.pt-BR.vtt

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13. Minimizing Error Functions.html

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14. Mean vs Total Error.html

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15. Mini-batch Gradient Descent.html

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16. Quiz Mini-Batch Gradient Descent.html

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17. Absolute Error vs Squared Error.html

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17. Absolute Vs Squared Error-csvdjaqt1GM.en.vtt

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17. Absolute Vs Squared Error-csvdjaqt1GM.mp4

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17. Absolute Vs Squared Error-csvdjaqt1GM.pt-BR.vtt

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17. DLND REG 12 Absolute Vs Squared Error 2 V1 (1)-7El1OH17Oi4.en.vtt

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17. DLND REG 12 Absolute Vs Squared Error 2 V1 (1)-7El1OH17Oi4.mp4

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17. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY.en.vtt

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17. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY.mp4

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17. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY.pt-BR.vtt

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18. Linear Regression in scikit-learn.html

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19. Higher Dimensions--UvpQV1qmiE.en.vtt

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19. Higher Dimensions--UvpQV1qmiE.mp4

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19. Higher Dimensions--UvpQV1qmiE.pt-BR.vtt

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19. Higher Dimensions.html

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20. Multiple Linear Regression.html

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21. Closed Form Solution-G3fRVgLa5gI.en.vtt

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21. Closed Form Solution-G3fRVgLa5gI.mp4

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21. Closed Form Solution-G3fRVgLa5gI.pt-BR.vtt

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21. Closed Form Solution.html

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22. (Optional) Closed form Solution Math.html

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23. Linear Regression Warnings.html

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24. Polynomial Regression-DBhWG-PagEQ.en.vtt

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24. Polynomial Regression-DBhWG-PagEQ.mp4

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24. Polynomial Regression-DBhWG-PagEQ.pt-BR.vtt

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24. Polynomial Regression.html

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25. Quiz Polynomial Regression.html

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26. Regularization-PyFNIcsNma0.en.vtt

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26. Regularization-PyFNIcsNma0.mp4

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26. Regularization-PyFNIcsNma0.pt-BR.vtt

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26. Regularization.html

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27. Quiz Regularization.html

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28. Feature Scaling.html

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29. Outro.html

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index.html

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/img/

batch-stochastic.png

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codecogseqn-61.gif

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e.gif

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just-a-simple-lin-reg.png

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l2-gradient-descent-data.png

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lin-reg-no-outliers.png

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lin-reg-w-outliers.png

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m.gif

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minibatch.png

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quadraticlinearregression.png

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quiz.jpg

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y.gif

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/Part 02-Module 01-Lesson 03_Perceptron Algorithm/

01. Intro.html

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01. Perception Algorithm V2-ebIlG6Pqwas.en.vtt

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01. Perception Algorithm V2-ebIlG6Pqwas.mp4

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01. Perception Algorithm V2-ebIlG6Pqwas.pt-BR.vtt

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01. Perception Algorithm V2-ebIlG6Pqwas.zh-CN.vtt

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02. Classification Problems 1.html

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02. Classsification Example-Dh625piH7Z0.en.vtt

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02. Classsification Example-Dh625piH7Z0.mp4

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03. Classification Example-46PywnGa_cQ.en.vtt

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03. Classification Example-46PywnGa_cQ.mp4

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03. Classification Example-46PywnGa_cQ.pt-BR.vtt

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03. Classification Example-46PywnGa_cQ.zh-CN.vtt

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03. Classification Problems 2.html

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04. Linear Boundaries-X-uMlsBi07k.en.vtt

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04. Linear Boundaries-X-uMlsBi07k.mp4

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04. Linear Boundaries-X-uMlsBi07k.pt-BR.vtt

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04. Linear Boundaries-X-uMlsBi07k.zh-CN.vtt

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04. Linear Boundaries.html

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05. 09 Higher Dimensions-eBHunImDmWw.en.vtt

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05. 09 Higher Dimensions-eBHunImDmWw.mp4

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05. Higher Dimensions.html

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06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.en.vtt

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06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp4

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06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.zh-CN.vtt

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06. Perceptrons.html

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07. AND And OR Perceptrons-45K5N0P9wJk.en.vtt

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07. AND And OR Perceptrons-45K5N0P9wJk.mp4

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07. AND And OR Perceptrons-45K5N0P9wJk.zh-CN.vtt

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07. Perceptrons as Logical Operators.html

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07. XOR Perceptron-TF83GfjYLdw.en.vtt

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08. Perceptron Trick.html

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09. Perceptron Agorithm Pseudocode-p8Q3yu9YqYk.en.vtt

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09. Perceptron Algorithm.html

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10. Outro.html

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index.html

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/img/

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/Part 02-Module 01-Lesson 04_Decision Trees/

01. Intro.html

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01. MLND SL DT 00 Intro V2-l34ijtQhVNk.en.vtt

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02. MLND SL DT 01 Recommending Apps 1 MAIN V3-uI_yNrqqKVg.en.vtt

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02. Recommending Apps 1.html

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03. Recommending Apps 2.html

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04. Recommending Apps-nEvW8B1HNq4.mp4

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05. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.en.vtt

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05. Quiz Student Admissions.html

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06. Solution Student Admissions.html

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06. Student Admissions-TdgBi6LtOB8.mp4

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07. Entropy-piLpj1V1HEk.en.vtt

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07. Entropy.html

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08. Entropy Formula 1.html

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11. Quiz Do You Know Your Entropy.html

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12. Multiclass Entropy.html

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13. MLND SL DT 10 Q Information Gain MAIN V1-tVLOLPEtLFw.en.vtt

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14. Solution Information Gain.html

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15. Maximizing Information Gain.html

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16. Calculating Information Gain on a Dataset.html

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17. Hyperparameters.html

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18. Decision Trees in sklearn.html

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19. Titanic Survival Model with Decision Trees.html

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20. [Solution] Titanic Survival Model.html

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21. Outro.html

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index.html

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/Part 02-Module 01-Lesson 05_Naive Bayes/

01. Intro.html

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02. Guess the Person.html

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03. Known and Inferred.html

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04. Guess the Person Now.html

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05. Bayes Theorem.html

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06. Quiz False Positives.html

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07. Solution False Positives.html

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08. Bayesian Learning 1.html

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09. Bayesian Learning 2.html

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10. Bayesian Learning 3.html

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11. MLND SL NB Naive Bayes Algorithm-CQBMB9jwcp8.en.vtt

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11. Naive Bayes Algorithm 1.html

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12. Naive Bayes Algorithm 2.html

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13. Quiz Bayes Rule .html

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14. Building a Spam Classifier.html

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15. Spam Classifier - Workspace.html

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16. Outro.html

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index.html

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/img/

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/Part 02-Module 01-Lesson 06_Support Vector Machines/

01. Intro.html

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01. Support Vector Machine V2-LBmM6pZCrI0.en.vtt

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01. Support Vector Machine V2-LBmM6pZCrI0.mp4

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02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.en.vtt

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02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.mp4

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02. Which line is better.html

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03. Minimizing Distances.html

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04. Error Function Intuition.html

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05. Perceptron Algorithm.html

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06. Classification Error.html

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07. Margin Error.html

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08. (Optional) Margin Error Calculation.html

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09. Error Function.html

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09. SVM 07 Error Function V1-A1wbrcSYc1c.mp4

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10. SVM 08 The C Parameter V2-6CxPhVo0hRw.en.vtt

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10. SVM 08 The C Parameter V2-6CxPhVo0hRw.zh-CN.vtt

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10. The C Parameter.html

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11. Polynomial Kernel 1.html

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11. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.en.vtt

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12. Polynomial Kernel 2.html

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13. Polynomial Kernel 3.html

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14. RBF Kernel 1.html

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15. RBF Kernel 2.html

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16. RBF Kernel 3.html

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16. SVM 14 RBF Kernel 3 V1-DctkE8kaWPY.zh-CN.vtt

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17. SVMs in sklearn.html

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18. Recap Additional Resources.html

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index.html

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/img/

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/Part 02-Module 01-Lesson 07_Ensemble Methods/

01. Intro.html

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01. MLND SL EM 01 Intro V1 MAIN V2-5v9KqIo6CFE.en.vtt

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02. Ensembles.html

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03. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.zh-CN.vtt

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03. Random Forests.html

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04. Bagging.html

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09. MLND SL EM 07 Weighting The Models 3 V1 MAIN V1-fecp5nmetws.en.vtt

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10. Combining the Models.html

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10. MLND SL EM 08 Combining The Models V1 MAIN V1-1GxscvKU2Ic.en.vtt

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11. AdaBoost in sklearn.html

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12. More Spam Classifying.html

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13. Recap Additional Resources.html

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index.html

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/Part 02-Module 01-Lesson 08_Model Evaluation Metrics/

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01. 01 Intro-4C4PuJANIdE.mp4

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01. Intro.html

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02. Outline.html

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03. Testing your models.html

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03. Testing-gmxGRJSKEb0.mp4

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04. Confusion Matrix-Question 1-9GLNjmMUB_4.en-US.vtt

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09. 04 Quiz False Negatives And Positives SC V1-_ytP9zIkziw.en.vtt

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14. 09 Quiz Fbeta Score SC V1-KSswld4_9bY.en.vtt

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18. Sklearn Practice (Regression).html

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19. Text Recap.html

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/Part 02-Module 01-Lesson 09_Training and Tuning/

01. 04 L Types Of Errors-Twf1qnPZeSY.en-US.vtt

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02. Model Complexity Graph-Question-YS5OQCA5cLY.en-US.vtt

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03. Cross Validation.html

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06. Detecting Overfitting and Underfitting with Learning Curves.html

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11. [Solution] Grid Search Lab.html

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/Part 02-Module 01-Lesson 10_Finding Donors Project/

01. ML Charity Project-aVodYHcOB8U.en.vtt

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01. ML Charity Project-aVodYHcOB8U.mp4

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01. Overview.html

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Project Description - Finding Donors for CharityML.html

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index.html

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/Part 03-Module 01-Lesson 01_Introduction to Neural Networks/

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02. Introduction.html

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07. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.en.vtt

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26. Pre-Lab Gradient Descent.html

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27. Notebook Gradient Descent.html

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32. 29 Neural Network Architecture 2-FWN3Sw5fFoM.en.vtt

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32. Neural Network Architecture.html

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35. Pre-Lab Analyzing Student Data.html

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36. Notebook Analyzing Student Data.html

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37. Outro.html

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index.html

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/Part 03-Module 01-Lesson 02_Implementing Gradient Descent/

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04. Gradient Descent The Code.html

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06. Multilayer Perceptrons.html

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/Part 03-Module 01-Lesson 03_Training Neural Networks/

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/Part 03-Module 01-Lesson 04_Keras/

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02. Keras.html

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03. Pre-Lab Student Admissions in Keras.html

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06. Mini Project Intro.html

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index.html

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/Part 03-Module 01-Lesson 05_Deep Learning with PyTorch/

01. Instructor.html

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02. Introducing PyTorch.html

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03. Part 1 V2-n4mbZYIfKb4.en.vtt

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03. PyTorch Tensors.html

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04. Defining Networks.html

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05. Training Networks.html

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06. Fashion-MNIST Exercise.html

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06. PyTorch - Part 4-AEJV_RKZ7VU.en.vtt

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08. Saving and Loading Trained Networks.html

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10. Transfer Learning.html

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/Part 03-Module 01-Lesson 06_Image Classifier Project/

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02. Introduction to GPU Workspaces.html

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03. Image Classifier - Part 1 - Development.html

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07. Rubric.html

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Project Description - Create Your Own Image Classifier.html

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index.html

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/Part 04-Module 01-Lesson 01_Clustering/

01. Introduction-k7YOVTkFRJM.en.vtt

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01. Introduction-k7YOVTkFRJM.mp4

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01. Introduction-k7YOVTkFRJM.pt-BR.vtt

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01. Video Introduction.html

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02. Text Course Outline.html

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03. Two Types of Unsupervised Learning-aHK_rpaS_ts.en.vtt

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03. Two Types of Unsupervised Learning-aHK_rpaS_ts.mp4

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03. Two Types of Unsupervised Learning-aHK_rpaS_ts.pt-BR.vtt

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03. Video Two Types of Unsupervised Learning.html

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04. 04 KMeans Use Cases 1 1 V2-25paySwVdAA.en.vtt

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04. 04 KMeans Use Cases 1 1 V2-25paySwVdAA.mp4

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04. 04 KMeans Use Cases 1 1 V2-25paySwVdAA.pt-BR.vtt

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04. Video K-Means Use Cases.html

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05. KMeans-B9jdQFpPEk0.en.vtt

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05. KMeans-B9jdQFpPEk0.mp4

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05. KMeans-B9jdQFpPEk0.pt-BR.vtt

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05. Video K-Means.html

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06. Quiz Identifying Clusters.html

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07. 07 Changing K 1 V3-Bd3M-xUlqEI.en.vtt

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07. 07 Changing K 1 V3-Bd3M-xUlqEI.mp4

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07. 07 Changing K 1 V3-Bd3M-xUlqEI.pt-BR.vtt

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07. Video Changing K.html

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08. Elbow Method For Finding K-e7fqXpo63n8.en.vtt

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08. Elbow Method For Finding K-e7fqXpo63n8.mp4

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08. Elbow Method For Finding K-e7fqXpo63n8.pt-BR.vtt

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08. Video Elbow Method.html

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09. 10 KMeans In Scikit Learn V1-jkEgQLOcCGo.en.vtt

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09. 10 KMeans In Scikit Learn V1-jkEgQLOcCGo.mp4

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09. 10 KMeans In Scikit Learn V1-jkEgQLOcCGo.pt-BR.vtt

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09. Screencast K-Means in Scikit Learn.html

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10. Notebook Your Turn.html

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11. 12 KMeans In Scikit Learn Solution V1-IIVsWFq2DXk.en.vtt

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11. 12 KMeans In Scikit Learn Solution V1-IIVsWFq2DXk.mp4

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11. 12 KMeans In Scikit Learn Solution V1-IIVsWFq2DXk.pt-BR.vtt

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11. Screencast Solution.html

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12. How Does K-Means Work-pL-pMCDgJuw.en.vtt

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12. How Does K-Means Work-pL-pMCDgJuw.mp4

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12. How Does K-Means Work-pL-pMCDgJuw.pt-BR.vtt

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12. Video How Does K-Means Work.html

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13. 14 How Does KMeans Work V1-y7yZyyHgyYU.en.vtt

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13. 14 How Does KMeans Work V1-y7yZyyHgyYU.mp4

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13. 14 How Does KMeans Work V1-y7yZyyHgyYU.pt-BR.vtt

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13. Screencast + Text How Does K-Means Work.html

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14. How Does K-Means Work.html

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15. Is That The Optimal Solution-g5aPtCpBNmw.en.vtt

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15. Is That The Optimal Solution-g5aPtCpBNmw.mp4

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15. Is That The Optimal Solution-g5aPtCpBNmw.pt-BR.vtt

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15. Video Is that the Optimal Solution.html

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16. Feature Scaling-rpTVp7C8AXo.en.vtt

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16. Feature Scaling-rpTVp7C8AXo.mp4

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16. Feature Scaling-rpTVp7C8AXo.pt-BR.vtt

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16. Video Feature Scaling.html

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17. Feature Scaling Example--Axyt0bPCT0.en.vtt

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17. Feature Scaling Example--Axyt0bPCT0.mp4

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17. Feature Scaling Example--Axyt0bPCT0.pt-BR.vtt

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17. Video Feature Scaling Example.html

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18. Notebook Feature Scaling Example.html

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19. Notebook Feature Scaling.html

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20. 19 Feature Scaling Solution V1-xddMZP2SQ1U.en.vtt

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20. 19 Feature Scaling Solution V1-xddMZP2SQ1U.mp4

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20. 19 Feature Scaling Solution V1-xddMZP2SQ1U.pt-BR.vtt

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20. Screencast Solution.html

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21. Outro-AeDSl4KSVIE.en.vtt

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21. Outro-AeDSl4KSVIE.mp4

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21. Outro-AeDSl4KSVIE.pt-BR.vtt

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21. Video Outro.html

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22. Text Recap.html

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index.html

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/Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/

01. K-means considerations.html

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01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.en.vtt

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01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.mp4

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01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.pt-BR.vtt

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01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.zh-CN.vtt

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02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.en.vtt

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02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.mp4

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02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.pt-BR.vtt

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02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.zh-CN.vtt

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02. Overview of other clustering methods.html

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03. Hierarchical clustering single-link.html

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03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.en.vtt

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03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.mp4

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03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.pt-BR.vtt

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03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.zh-CN.vtt

5.5 KB

04. Examining single-link clustering.html

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04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.en.vtt

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04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.mp4

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04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.pt-BR.vtt

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04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.zh-CN.vtt

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05. Complete-link, average-link, Ward.html

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05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.en.vtt

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05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.mp4

23.6 MB

05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.pt-BR.vtt

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05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.zh-CN.vtt

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06. Hierarchical clustering implementation.html

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06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.en.vtt

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06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.mp4

7.8 MB

06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.pt-BR.vtt

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06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.zh-CN.vtt

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07. [Lab] Hierarchical clustering .html

6.9 KB

08. [Lab Solution] Hierarchical Clustering.html

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09. HC examples and applications.html

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09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.en.vtt

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09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.mp4

9.6 MB

09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.pt-BR.vtt

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09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.zh-CN.vtt

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10. [Quiz] Hierarchical clustering.html

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11. DBSCAN.html

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11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.en.vtt

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11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.mp4

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11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.pt-BR.vtt

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11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.zh-CN.vtt

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12. DBSCAN implementation.html

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12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.en.vtt

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12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.mp4

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12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.pt-BR.vtt

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12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.zh-CN.vtt

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13. [Lab] DBSCAN.html

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14. [Lab Solution] DBSCAN.html

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15. DBSCAN examples applications.html

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15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.en.vtt

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15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.mp4

18.6 MB

15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.pt-BR.vtt

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15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.zh-CN.vtt

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16. [Quiz] DBSCAN.html

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index.html

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/Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/

01. Intro.html

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01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.en.vtt

2.3 KB

01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.mp4

8.8 MB

01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.pt-BR.vtt

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01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.zh-CN.vtt

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02. Gaussian Mixture Model (GMM) Clustering.html

7.5 KB

02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.en.vtt

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02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.mp4

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02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.pt-BR.vtt

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02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.zh-CN.vtt

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03. Gaussian Distribution in One Dimension.html

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03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.en.vtt

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03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.mp4

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03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.pt-BR.vtt

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03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.zh-CN.vtt

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04. GMM Clustering in One Dimension.html

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04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.en.vtt

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04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.mp4

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04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.pt-BR.vtt

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04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.zh-CN.vtt

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05. Gaussian Distribution in 2D.html

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05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.en.vtt

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05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.mp4

7.3 MB

05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.pt-BR.vtt

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05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.zh-CN.vtt

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06. GMM in 2D.html

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06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.en.vtt

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06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.mp4

6.3 MB

06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.pt-BR.vtt

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06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.zh-CN.vtt

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07. Quiz Gaussian Mixtures.html

10.3 KB

08. Overview of The Expectation Maximization (EM) Algorithm.html

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09. Expectation Maximization Part 1.html

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09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.en.vtt

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09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.mp4

34.2 MB

09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.pt-BR.vtt

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09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.zh-CN.vtt

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10. Expectation Maximization Part 2.html

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10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.en.vtt

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10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.mp4

27.6 MB

10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.pt-BR.vtt

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10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.zh-CN.vtt

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11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.en.vtt

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11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.mp4

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11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.pt-BR.vtt

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11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.zh-CN.vtt

2.9 KB

11. Visual Example of EM Progress.html

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12. Quiz Expectation Maximization.html

7.4 KB

13. GMM Implementation.html

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13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.en.vtt

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13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.mp4

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13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.pt-BR.vtt

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13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.zh-CN.vtt

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14. GMM Examples Applications.html

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14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.en.vtt

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14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.mp4

33.2 MB

14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.pt-BR.vtt

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14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.zh-CN.vtt

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15. Cluster Analysis Process.html

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15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.en.vtt

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15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.mp4

12.3 MB

15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.pt-BR.vtt

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15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.zh-CN.vtt

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16. Cluster Validation.html

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16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.en.vtt

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16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.mp4

6.1 MB

16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.pt-BR.vtt

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16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.zh-CN.vtt

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17. External Validation Indices.html

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17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.en.vtt

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17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.mp4

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17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.pt-BR.vtt

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17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.zh-CN.vtt

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18. Quiz Adjusted Rand Index.html

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19. Internal Validation Indices.html

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19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.en.vtt

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19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.mp4

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19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.pt-BR.vtt

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19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.zh-CN.vtt

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20. Quiz Silhouette Coefficient .html

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21. GMM Cluster Validation Lab.html

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22. GMM Cluster Validation Lab Solution.html

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index.html

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/img/

external-indices-quiz.png

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gmm-1d-quiz.png

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gmm-2d-quiz.png

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gmm-quiz.png

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/Part 04-Module 01-Lesson 04_PCA/

01. Introduction-tpFPcxoGxaE.en.vtt

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01. Introduction-tpFPcxoGxaE.mp4

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01. Introduction-tpFPcxoGxaE.pt-BR.vtt

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01. Video Introduction.html

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02. Lesson Topics-LBzA08F_r4w.en.vtt

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02. Lesson Topics-LBzA08F_r4w.mp4

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02. Lesson Topics-LBzA08F_r4w.pt-BR.vtt

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02. Video Lesson Topics.html

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03. Text Lesson Topics.html

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04. Latent Features-kYLcVgpEwGs.en.vtt

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04. Latent Features-kYLcVgpEwGs.mp4

1.8 MB

04. Latent Features-kYLcVgpEwGs.pt-BR.vtt

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04. Video Latent Features.html

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05. Latent Features.html

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06. How to Reduce Features-ydhrelgjriI.en.vtt

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06. How to Reduce Features-ydhrelgjriI.mp4

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06. How to Reduce Features-ydhrelgjriI.pt-BR.vtt

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06. Video How to Reduce Features.html

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07. Dimensionality Reduction-mANti9veGtc.en.vtt

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07. Dimensionality Reduction-mANti9veGtc.mp4

3.1 MB

07. Dimensionality Reduction-mANti9veGtc.pt-BR.vtt

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07. Video Dimensionality Reduction.html

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08. PCA Properties-1oaaq-0wdB0.en.vtt

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08. PCA Properties-1oaaq-0wdB0.mp4

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08. PCA Properties-1oaaq-0wdB0.pt-BR.vtt

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08. Video PCA Properties.html

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09. Quiz How Does PCA Work.html

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10. 09 PCA V1-0RLDZWeq5JE.en.vtt

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10. 09 PCA V1-0RLDZWeq5JE.mp4

13.4 MB

10. 09 PCA V1-0RLDZWeq5JE.pt-BR.vtt

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10. Screencast PCA.html

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11. Notebook PCA - Your Turn.html

7.3 KB

12. 11 PCA 1 Solution V1-u0rJRmubQ44.en.vtt

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12. 11 PCA 1 Solution V1-u0rJRmubQ44.mp4

21.2 MB

12. 11 PCA 1 Solution V1-u0rJRmubQ44.pt-BR.vtt

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12. Screencast PCA Solution.html

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13. 12 Interpret PCA Results V1-ZX6EACfsZbc.en.vtt

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13. 12 Interpret PCA Results V1-ZX6EACfsZbc.mp4

5.3 MB

13. 12 Interpret PCA Results V1-ZX6EACfsZbc.pt-BR.vtt

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13. Screencast Interpret PCA Results.html

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14. Notebook Interpretation.html

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15. 14 Interpretation Solution V1-wU2duZa0ds0.en.vtt

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15. 14 Interpretation Solution V1-wU2duZa0ds0.mp4

9.6 MB

15. 14 Interpretation Solution V1-wU2duZa0ds0.pt-BR.vtt

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/Part 04-Module 01-Lesson 05_Random Projection and ICA/

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/Part 04-Module 01-Lesson 06_Project Identify Customer Segments/

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/Part 05-Module 01-Lesson 01_Congratulations!/

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/Part 06-Module 01-Lesson 01_Why Python Programming/

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/Part 06-Module 01-Lesson 02_Data Types and Operators/

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/Part 06-Module 01-Lesson 03_Control Flow/

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25. Break, Continue.html

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27. Solution Break, Continue.html

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28. Zip and Enumerate-bSJPzVArE7M.ar.vtt

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28. Zip and Enumerate.html

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29. Quiz Zip and Enumerate.html

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30. Solution Zip and Enumerate.html

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31. List Comprehensions-6qxo-NV9v_s.ar.vtt

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32. Quiz List Comprehensions.html

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33. Solution List Comprehensions.html

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34. Conclusion.html

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34. Congrats!-vDoqpwCHxs4.ar.vtt

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index.html

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/Part 06-Module 01-Lesson 04_Functions/

01. Introduction-p5L4rTV1Pgk.ar.vtt

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01. Introduction-p5L4rTV1Pgk.en.vtt

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01. Introduction-p5L4rTV1Pgk.mp4

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01. Introduction-p5L4rTV1Pgk.pt-BR.vtt

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01. Introduction.html

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02. Default Arguments-cG6UfBZX2KI.ar.vtt

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02. Defining Functions-IP_tJYhynbc.ar.vtt

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02. Defining Functions.html

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03. Quiz Defining Functions.html

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04. Solution Defining Functions.html

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05. Variable Scope-rYubQlAM-gw.ar.vtt

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05. Variable Scope.html

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07. Solution Variable Scope.html

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08. Documentation-_Vl9NJkA6JQ.ar.vtt

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08. Documentation.html

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09. Quiz Documentation.html

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10. Solution Documentation.html

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11. L4 08 Lambda Expressions V3-wkEmPz1peJM.en.vtt

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11. Lambda Expressions.html

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12. Quiz Lambda Expressions.html

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13. Solution Lambda Expressions.html

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14. Iterators And Generators-tYH8X4Zeh-0.ar.vtt

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14. Iterators And Generators-tYH8X4Zeh-0.mp4

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14. [Optional] Iterators and Generators.html

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15. [Optional] Quiz Iterators and Generators.html

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16. [Optional] Solution Iterators and Generators.html

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17. [Optional] Generator Expressions.html

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18. Conclusion-QRnLr7pwHyk.ar.vtt

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18. Conclusion.html

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19. Further Learning.html

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index.html

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/Part 06-Module 01-Lesson 05_Scripting/

01. Introduction.html

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01. Scripting-Qxe_gCiXUDg.ar.vtt

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01. Scripting-Qxe_gCiXUDg.mp4

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02. Python Installation-2_P05aYChqQ.ar.vtt

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02. Python Installation.html

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03. Install Python Using Anaconda.html

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04. [For Windows] Configuring Git Bash to Run Python.html

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05. Running A Python Script-vMKemwCderg.ar.vtt

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05. Running a Python Script.html

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06. Programming Environment Setup-EKxDnCK0NAk.ar.vtt

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06. Programming Environment Setup-EKxDnCK0NAk.mp4

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06. Programming Environment Setup.html

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07. Editing a Python Script.html

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08. Scripting With Raw Input-Fs9uLV2qfgI.ar.vtt

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08. Scripting with Raw Input.html

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09. Quiz Scripting with Raw Input.html

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10. Solution Scripting with Raw Input.html

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11. Errors And Exceptions-DmthSiy2d0U.ar.vtt

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13. Handling Error Specifying Exceptions-EHW5I7shdJg.ar.vtt

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13. Handling Errors Try Except Finally-S6hwBZG0KwM.ar.vtt

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13. Handling Errors.html

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14. Practice Handling Input Errors.html

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15. Solution Handling Input Errors.html

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16. Accessing Error Messages.html

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17. Reading And Writing Files Part II-1GRv1S6K8gQ.ar.vtt

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17. Reading And Writing Files Using With-OQ-Y0mMjm00.ar.vtt

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17. Reading and Writing Files.html

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18. Quiz Reading and Writing Files.html

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19. Solution Reading and Writing Files.html

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20. Importing Files-qjeSn6zZbR0.ar.vtt

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20. Importing Local Scripts.html

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21. The Standard Library-Fw3vf0tDrJM.ar.vtt

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21. The Standard Library-Fw3vf0tDrJM.mp4

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21. The Standard Library.html

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22. Quiz The Standard Library.html

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23. Solution The Standard Library.html

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24. Techniques For Importing Modules Part II-aASigWQ_XU0.ar.vtt

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24. Techniques For Importing Modules-jPGyFgcIvsM.ar.vtt

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24. Techniques for Importing Modules.html

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25. Quiz Techniques for Importing Modules.html

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26. Third Party Libraries And Package Managers-epOze9gC6T4.ar.vtt

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26. Third Party Libraries And Package Managers-epOze9gC6T4.mp4

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26. Third-Party Libraries.html

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27. Experimenting With An Interpreter-hspPtnQwMPg.ar.vtt

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27. Experimenting With An Interpreter-hspPtnQwMPg.mp4

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27. Experimenting with an Interpreter.html

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28. Online Resources.html

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29. Conclusion-rEMrswkLvh8.ar.vtt

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29. Conclusion.html

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index.html

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/img/

generate-messages-output.png

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step1-cd.png

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step2-pwd.png

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/Part 06-Module 01-Lesson 06_NumPy/

01. Instructors.html

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02. Introduction to NumPy.html

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03. NumPy 0 V1-vyjMs8KFHlE.en.vtt

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03. NumPy 0 V1-vyjMs8KFHlE.mp4

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03. Why Use NumPy.html

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04. Creating and Saving NumPy ndarrays.html

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04. NumPy 1 V1-EOHW29kDg7w.en.vtt

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04. NumPy 1 V1-EOHW29kDg7w.mp4

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05. Using Built-in Functions to Create ndarrays.html

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06. Create an ndarray.html

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07. Accessing, Deleting, and Inserting Elements Into ndarrays.html

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07. NumPy 3 V1-Rt4aydeo9F8.en.vtt

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08. Slicing ndarrays.html

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09. Boolean Indexing, Set Operations, and Sorting.html

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09. NumPy 5 V1-vGjI-WTnEbY.en.vtt

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10. Manipulating ndarrays.html

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11. Arithmetic operations and Broadcasting.html

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12. Creating ndarrays with Broadcasting.html

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13. Getting Set Up for the Mini-Project.html

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14. Mini-Project Mean Normalization and Data Separation.html

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index.html

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/img/

screen-shot-2018-03-19-at-2.30.59-pm.png

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/Part 06-Module 01-Lesson 07_Pandas/

01. Instructors.html

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02. Introduction to Pandas.html

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03. Why Use Pandas.html

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04. Creating Pandas Series.html

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04. Pandas 1 V1-iXnYN8cnhzs.en.vtt

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08. Creating Pandas DataFrames.html

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10. Dealing with NaN.html

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11. Manipulate a DataFrame.html

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12. Loading Data into a Pandas DataFrame.html

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13. Getting Set Up for the Mini-Project.html

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14. Mini-Project Statistics From Stock Data.html

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index.html

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/img/

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/Part 07-Module 01-Lesson 01_Basic SQL/

01. Introduction-Z8WNfx9Oq9s.ar.vtt

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01. Introduction-Z8WNfx9Oq9s.mp4

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01. Introduction-Z8WNfx9Oq9s.zh-CN.vtt

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01. Video SQL Introduction.html

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02. Parch Posey Database-JOMI560DgXg.ar.vtt

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/Part 07-Module 01-Lesson 02_SQL Joins/

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01. Video Motivation.html

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03. Video Introduction to JOINs.html

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06. Text ERD Reminder.html

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07. Text Primary and Foreign Keys.html

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/Part 07-Module 01-Lesson 03_SQL Aggregations/

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25. DATE Functions I-E7Z6GMFVmIY.ar.vtt

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/Part 07-Module 01-Lesson 04_SQL Subqueries Temporary Tables/

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/Part 07-Module 01-Lesson 05_SQL Data Cleaning/

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05. Video POSITION, STRPOS, SUBSTR.html

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/Part 07-Module 01-Lesson 06_[Advanced] SQL Window Functions/

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02. Video Window Functions 1.html

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07. Video ROW_NUMBER RANK.html

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10. Aggregates in Window Functions-Dxew5w3VF7k.ar.vtt

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/Part 07-Module 01-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/

01. Introduction to Advanced SQL-i0VaVPIKUks.ar.vtt

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01. Video Introduction to Advanced SQL.html

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02. Text + Images FULL OUTER JOIN.html

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03. Quiz FULL OUTER JOIN.html

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04. Solutions FULL OUTER JOIN.html

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05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.ar.vtt

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18. Joining Subqueries-rxy-fE5GeLY.ar.vtt

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/Part 08-Module 01-Lesson 01_Data Visualization in Data Analysis/

01. Introduction to Data Visualization.html

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01. L1 011 Data Visualization In Data Analysis Intro V3 V3-U1VapEELBfw.mp4

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02. Motivation for Data Visualization.html

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03. Further Motivation.html

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04. Exploratory vs. Explanatory Analyses.html

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05. Quiz Exploratory vs. Explanatory.html

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06. L1 061 Visualization In Python V1-MFS-1veFC_c.mp4

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06. Visualization in Python.html

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07. Course Structure.html

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08. L1 08.1 Lesson Summary HD (1)--c9IeqHkAZ0.mp4

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/img/

mike-josh-bios-portraits.png

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/Part 08-Module 01-Lesson 02_Design of Visualizations/

01. Introduction.html

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01. L2 011 Intro HD V2-TlpGWQBLG6E.mp4

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01. L2 011 Intro HD V2-TlpGWQBLG6E.pt-BR.vtt

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02. What Makes a Bad Visual-zbvB_9f7bFs.ar.vtt

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02. What Makes a Bad Visual-zbvB_9f7bFs.en.vtt

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02. What Makes a Bad Visual-zbvB_9f7bFs.mp4

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02. What Makes a Bad Visual-zbvB_9f7bFs.pt-BR.vtt

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02. What Makes a Bad Visual-zbvB_9f7bFs.zh-CN.vtt

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02. What Makes a Bad Visual.html

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03. L2 031 Levels Of Measurement And Types Of Data V6-3Plhn5Q4xIA.mp4

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03. L2 031 Levels Of Measurement And Types Of Data V6-3Plhn5Q4xIA.pt-BR.vtt

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03. Levels of Measurement Types of Data.html

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04. Quiz Data Types (Quantitative vs. Categorical).html

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05. Text + Quiz Data Types (Ordinal vs. Nominal).html

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06. Data Types (Continuous vs. Discrete).html

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07. Identifying Data Types.html

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08. What Experts Say About Visual Encodings-98aog0eVcC4.ar.vtt

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08. What Experts Say About Visual Encodings-98aog0eVcC4.mp4

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08. What Experts Say About Visual Encodings-98aog0eVcC4.zh-CN.vtt

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08. What Experts Say About Visual Encodings.html

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09. Chart Junk-3BTBEYOG2o8.ar.vtt

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09. Chart Junk-3BTBEYOG2o8.mp4

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09. Chart Junk.html

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10. Data Ink Ratio-gW2FapuYV4A.ar.vtt

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10. Data Ink Ratio-gW2FapuYV4A.mp4

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10. Data Ink Ratio-gW2FapuYV4A.zh-CN.vtt

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10. Data Ink Ratio.html

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11. Design Integrity-y72_fVFtqlY.ar.vtt

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11. Design Integrity-y72_fVFtqlY.mp4

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11. Design Integrity.html

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12. Bad Visual Quizzes (Part I).html

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13. Bad Visual Quizzes (Part II).html

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14. Using Color-6bAedqD3ilw.en.vtt

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14. Using Color-6bAedqD3ilw.mp4

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14. Using Color-6bAedqD3ilw.pt-BR.vtt

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14. Using Color-6bAedqD3ilw.zh-CN.vtt

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14. Using Color.html

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15. Designing for Color Blindness-k4iTzS7t2U4.ar.vtt

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15. Designing for Color Blindness-k4iTzS7t2U4.en.vtt

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15. Designing for Color Blindness-k4iTzS7t2U4.mp4

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15. Designing for Color Blindness-k4iTzS7t2U4.zh-CN.vtt

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15. Designing for Color Blindness.html

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16. Shape, Size, Other Tools.html

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16. Shape, Size, and other Tools-fzEliHW3ZLM.ar.vtt

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16. Shape, Size, and other Tools-fzEliHW3ZLM.en.vtt

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16. Shape, Size, and other Tools-fzEliHW3ZLM.mp4

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16. Shape, Size, and other Tools-fzEliHW3ZLM.zh-CN.vtt

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17. Good Visual.html

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18. L2 181 Lesson Summary HDmp4 V3-kKEeBDs4HuM.mp4

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18. L2 181 Lesson Summary HDmp4 V3-kKEeBDs4HuM.pt-BR.vtt

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18. Lesson Summary.html

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index.html

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/img/

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apple.jpg

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bad-viz-2.png

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challenger2.gif

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/Part 08-Module 01-Lesson 03_Univariate Exploration of Data/

01. Introduction.html

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01. L3 011 Intro V3-4BpAF4MYKm8.en.vtt

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01. L3 011 Intro V3-4BpAF4MYKm8.mp4

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02. Tidy Data.html

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03. Bar Charts.html

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03. DataVis L3 03 V2-srRhFrSPdvs.en.vtt

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03. DataVis L3 03 V2-srRhFrSPdvs.mp4

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03. L3 031 Bar Charts V3-ybXcduB6cXA.en.vtt

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03. L3 031 Bar Charts V3-ybXcduB6cXA.mp4

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04. Absolute vs. Relative Frequency.html

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04. DataVis L3 04 V2-HLum_ys7RJ0.en.vtt

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04. DataVis L3 04 V2-HLum_ys7RJ0.mp4

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04. L3 041 Absolute V Relative Frequency V5-FpnZ7dH4FqU.en.vtt

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04. L3 041 Absolute V Relative Frequency V5-FpnZ7dH4FqU.mp4

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04. L3 041 Absolute V Relative Frequency V5-FpnZ7dH4FqU.zh-CN.vtt

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05. Counting Missing Data.html

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06. Bar Chart Practice.html

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07. L3 071 Pie Charts V3-kSrJGJHTKV8.en.vtt

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07. L3 071 Pie Charts V3-kSrJGJHTKV8.mp4

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07. L3 071 Pie Charts V3-kSrJGJHTKV8.zh-CN.vtt

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07. Pie Charts.html

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08. DataVis L3 08 V2-f1we_0dUSXg.en.vtt

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08. DataVis L3 08 V2-f1we_0dUSXg.mp4

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08. Histograms.html

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09. Histogram Practice.html

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10. Figures, Axes, and Subplots.html

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11. Choosing a Plot for Discrete Data.html

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12. DataVis L3 11 V1-C8DGwJa_adA.en.vtt

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12. DataVis L3 11 V1-C8DGwJa_adA.mp4

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12. Descriptive Statistics, Outliers and Axis Limits.html

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12. L3 111 Descriptive Stats Outliers And Axis Limits V2-kQoK7UwrGh0.en.vtt

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13. DataVis L3 12 V2-fo0VIbQRBJk.en.vtt

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13. DataVis L3 12 V2-fo0VIbQRBJk.mp4

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13. L3 121 Scales And Transformations V3-PE53ga2bOME.en.vtt

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13. L3 121 Scales And Transformations V3-PE53ga2bOME.mp4

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13. L3 121 Scales And Transformations V3-PE53ga2bOME.zh-CN.vtt

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13. Scales and Transformations.html

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14. Scales and Transformations Practice.html

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15. L3 141 Lesson Summary V1-7ZaSMbsJUWU.en.vtt

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15. L3 141 Lesson Summary V1-7ZaSMbsJUWU.mp4

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15. Lesson Summary.html

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16. Extra Kernel Density Estimation.html

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index.html

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/img/

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tidy-data-four.png

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tidy-data-three.png

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/Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/

01. Introduction.html

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01. L4 011 Intro V2-JzvJIWG8Rk4.en.vtt

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01. L4 011 Intro V2-JzvJIWG8Rk4.mp4

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01. L4 011 Intro V2-JzvJIWG8Rk4.zh-CN.vtt

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02. Data Vis L4 C02 V1-wBDC5AmYgyg.en.vtt

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02. Data Vis L4 C02 V1-wBDC5AmYgyg.mp4

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02. Data Vis L4 C02 V1-wBDC5AmYgyg.zh-CN.vtt

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02. L4 021 Scatterplots And Correlation V2-wqMwTDVT9_Y.en.vtt

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02. L4 021 Scatterplots And Correlation V2-wqMwTDVT9_Y.mp4

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02. L4 021 Scatterplots And Correlation V2-wqMwTDVT9_Y.zh-CN.vtt

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02. Scatterplots and Correlation.html

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03. Data Vis L4 C03 V1-0F6ldBC6Nbs.mp4

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03. L4 031 Overplotting Transparency And Jitter 1 V4-BGqR-nxgMtg.en.vtt

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03. Overplotting, Transparency, and Jitter.html

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04. Data Vis L4 C04 V1-O6ElT4IFXc0.en.vtt

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04. Data Vis L4 C04 V1-O6ElT4IFXc0.mp4

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04. Heat Maps.html

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04. L4 041 Heat Maps V4-RyCdvsmBjtE.mp4

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04. L4 041 Heat Maps V4-RyCdvsmBjtE.zh-CN.vtt

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05. Scatterplot Practice.html

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06. Data Vis L4 C06 V2-f8Kh4PByiEA.en.vtt

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06. L4 061 Violin Plots 2 V3-0hr61L-LZyM.en.vtt

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06. L4 061 Violin Plots 2 V3-0hr61L-LZyM.zh-CN.vtt

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06. Violin Plots.html

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07. Box Plots.html

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07. Data Vis L4 C07 V1-f6v3L3IDo24.mp4

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07. L4 071 Box Plots V4-3gxJag12T0g.en.vtt

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07. L4 071 Box Plots V4-3gxJag12T0g.zh-CN.vtt

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08. Violin and Box Plot Practice.html

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09. Clustered Bar Charts.html

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09. Data Vis L4 C09 V1-OnzWhpgM9Vs.en.vtt

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09. Data Vis L4 C09 V1-OnzWhpgM9Vs.mp4

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09. Data Vis L4 C09 V1-OnzWhpgM9Vs.zh-CN.vtt

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09. L4 091 Clustered Bar Charts V4-0rFp55TtEJM.en.vtt

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09. L4 091 Clustered Bar Charts V4-0rFp55TtEJM.mp4

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09. L4 091 Clustered Bar Charts V4-0rFp55TtEJM.zh-CN.vtt

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10. Categorical Plot Practice.html

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11. Data Vis L4 C11 V1-3Ls6w8Cd8n4.en.vtt

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11. Data Vis L4 C11 V1-3Ls6w8Cd8n4.zh-CN.vtt

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11. Faceting.html

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11. L4 111 Faceting V2-oUYRqI6wFGw.mp4

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11. L4 111 Faceting V2-oUYRqI6wFGw.zh-CN.vtt

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12. Adaptation of Univariate Plots.html

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12. Data Vis L4 C12 V2-aJncRqqJUYI.mp4

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12. Data Vis L4 C12 V2-aJncRqqJUYI.zh-CN.vtt

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12. L4 121 Adaptations Of Univariate Plots V3-MXcqplnUB0o.en.vtt

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12. L4 121 Adaptations Of Univariate Plots V3-MXcqplnUB0o.mp4

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12. L4 121 Adaptations Of Univariate Plots V3-MXcqplnUB0o.pt-BR.vtt

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12. L4 121 Adaptations Of Univariate Plots V3-MXcqplnUB0o.zh-CN.vtt

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13. Data Vis L4 C13 V1-Z7NjwA6jbjU.en.vtt

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13. Data Vis L4 C13 V1-Z7NjwA6jbjU.mp4

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13. Data Vis L4 C13 V1-Z7NjwA6jbjU.pt-BR.vtt

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13. Data Vis L4 C13 V1-Z7NjwA6jbjU.zh-CN.vtt

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13. L4 131 Line Plots V1-kSntEWPuOa0.en.vtt

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13. L4 131 Line Plots V1-kSntEWPuOa0.mp4

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13. L4 131 Line Plots V1-kSntEWPuOa0.zh-CN.vtt

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13. Line Plots.html

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14. Additional Plot Practice.html

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15. L4 151 Lesson Summary V1-5igqM44KEmw.en.vtt

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15. L4 151 Lesson Summary V1-5igqM44KEmw.mp4

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15. L4 151 Lesson Summary V1-5igqM44KEmw.zh-CN.vtt

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15. Lesson Summary.html

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16. Extra Swarm Plots.html

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17. Extra Rug and Strip Plots.html

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index.html

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/img/

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/Part 08-Module 01-Lesson 05_Multivariate Exploration of Data/

01. Introduction.html

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01. L5 011 Intro V3-ckylQMBXB10.en.vtt

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01. L5 011 Intro V3-ckylQMBXB10.mp4

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02. DataVis L5C02 V3-bgDNMfG9Gfs.en.vtt

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02. DataVis L5C02 V3-bgDNMfG9Gfs.mp4

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02. L5 021 Non Positional Encodings For Third Variables V1-D91mm-qaDkk.en.vtt

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03. Color Palettes.html

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03. L5 031 Color Palettes V1-nirOTWkuiSM.en.vtt

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04. Encodings Practice.html

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05. Faceting in Two Directions.html

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06. Other Adaptations of Bivariate Plots.html

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07. Adapted Plot Practice.html

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08. DataVis L5C08 V2-fq-hakwfpZw.mp4

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08. L5 081 Plot Matrices V3-2wY-euTIE5g.en.vtt

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09. Feature Engineering.html

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10. How Much is Too Much.html

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11. Additional Plot Practice.html

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index.html

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/img/

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/Part 08-Module 01-Lesson 06_Explanatory Visualizations/

01. Introduction.html

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01. L6 011 Intro V1-gLy8qpursJI.mp4

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02. Revisiting the Data Analysis Process.html

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03. Tell A Story.html

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04. Same Data, Different Stories.html

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05. Quizzes on Data Story Telling.html

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06. L6 061 Polishing Plots V3-4TixzVx79uk.mp4

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06. Polishing Plots.html

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07. Creating a Slide Deck with Jupyter.html

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08. Getting and Using Feedback.html

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09. L6 131 Lesson Summary V1-t6ss31RZF34.mp4

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index.html

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/img/

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/Part 08-Module 01-Lesson 07_Visualization Case Study/

01. Introduction.html

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01. L7 011 Intro V1-Virihwp36do.mp4

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02. Info on the Diamond Dataset.html

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03. Univariate Exploration.html

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04. Bivariate Exploration.html

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05. Multivariate Exploration.html

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06. Explanatory Polishing.html

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07. Conclusion.html

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index.html

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/Part 09-Module 01-Lesson 01_Shell Workshop/

01. Shell Intro--EtN5oD8MM0.ar.vtt

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01. Shell Intro--EtN5oD8MM0.mp4

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01. Welcome!.html

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02. Ud206 002 P0 Windows Installing Git Bash-UQZvV6VTlGQ.ar.vtt

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02. Windows Installing Git Bash.html

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03. Opening a terminal.html

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03. Ud206 003 Shell P1 - Opening A Terminal-4q6Vtym-nno.ar.vtt

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04. Ud206 004 Shell P2 - Your First Command-ggf5WhOYy1U.ar.vtt

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04. Your first command (echo).html

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05. Navigating directories (ls, cd, ..).html

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06. Current working directory (pwd).html

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06. Ud206 007 Shell P4 - Current Working Directory-X7dsy3oMHp0.ar.vtt

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07. Parameters and options (ls -l).html

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08. Organizing your files (mkdir, mv).html

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08. Ud206 009 Shell P6 - Organizing Your Files-NZsYyzzpJXA.ar.vtt

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09. Downloading (curl).html

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09. Ud206 011 Shell P7 - Downloading-h7FhU1f4TgE.ar.vtt

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09. Ud206 011 Shell P7.1 - Downloading Solution-1oEJUA-b0kE.ar.vtt

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10. Ud206 013 Shell P8 - Viewing Files-hPPVMKqbQV0.ar.vtt

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10. Viewing files (cat, less).html

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11. Removing things (rm, rmdir).html

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11. Ud206 014 Shell P9 - Removing Things-it19PvJarbk.ar.vtt

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12. Searching and pipes (grep, wc).html

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12. Ud206 016 Shell P10 - Searching And Pipes-AWpVScp9z4s.ar.vtt

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12. Ud206 016 Shell P10 - Searching And Pipes-AWpVScp9z4s.zh-CN.vtt

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13. Shell and environment variables.html

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13. Ud206 017 Shell P11 - Variables-Dx3WlMZk8iA.en.vtt

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13. Ud206 017 Shell P11 - Variables-Dx3WlMZk8iA.mp4

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14. Startup files (.bash_profile).html

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15. Controlling the shell prompt ($PS1).html

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15. Ud206 020 Shell P13 Controlling The Shell Prompt ($PS1)-nnqvRZ-Fx3k.ar.vtt

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15. Ud206 020 Shell P13 Controlling The Shell Prompt ($PS1)-nnqvRZ-Fx3k.zh-CN.vtt

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16. Aliases.html

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16. Ud206 021 Shell P14 Aliases-kINmpgXxayM.ar.vtt

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16. Ud206 021 Shell P14 Aliases-kINmpgXxayM.zh-CN.vtt

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17. Keep learning!.html

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17. Ud206 022 Shell Workshop Outro-68twTPXPrx0.ar.vtt

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index.html

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/Part 10-Module 01-Lesson 01_What is Version Control/

01. Gitfinal L1 01 Welcome-lbR82UD5F0c.ar.vtt

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01. Gitfinal L1 01 Welcome-lbR82UD5F0c.en.vtt

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01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.ar.vtt

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01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.mp4

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01. What is Version Control.html

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02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.ar.vtt

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02. Version Control In Daily Use.html

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03. Git and Version Control Terminology.html

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03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 15 Git The Big Picture-dVil8e0yptQ.ar.vtt

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04. MacLinux Setup.html

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05. Windows Setup.html

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/Part 10-Module 01-Lesson 02_Create A Git Repo/

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01. Intro.html

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02. Create A Repo From Scratch.html

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03. Clone An Existing Repo.html

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04. Determine A Repo's Status.html

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05. Outro.html

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/Part 10-Module 01-Lesson 03_Review a Repo's History/

01. A Repository's History - Intro-UBmg3syQS0E.ar.vtt

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01. Intro.html

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02. Displaying A Repository's Commits.html

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02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.ar.vtt

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03. Changing How Git Log Displays Information.html

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04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.ar.vtt

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04. Viewing Modified Files.html

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05. Viewing File Changes.html

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06. Viewing A Specific Commit.html

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07. Outro.html

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/Part 10-Module 01-Lesson 04_Add Commits To A Repo/

01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.ar.vtt

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01. Intro.html

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02. Git Add.html

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03. Git Commit.html

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04. Commit Messages.html

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05. Git Diff.html

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06. Having Git Ignore Files.html

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/img/

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/Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/

01. Intro.html

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02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.ar.vtt

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02. Tagging.html

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03. Branching.html

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04. Branching Effectively.html

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05. Merging.html

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06. Merge Conflicts.html

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/Part 10-Module 01-Lesson 06_Undoing Changes/

01. Intro.html

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02. Modifying The Last Commit.html

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03. Reverting A Commit.html

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04. Resetting Commits.html

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05. Lesson Outro.html

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/Part 10-Module 01-Lesson 07_Working With Remotes/

01. Intro-SBUOhyXcR1Q.ar.vtt

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01. Intro.html

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02. Remote Repositories.html

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03. Add A Remote Repository.html

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05. L1 - Git Pull In Theory-MjNU2LTDVAA.ar.vtt

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05. L1 - Git Pull In Theory-MjNU2LTDVAA.mp4

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05. Pulling Changes From A Remote.html

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06. L1 - Fetch Merge And Push-jwyQUfE1Eqw.ar.vtt

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06. Pull Vs Fetch-kxXdk2HcOBo.ar.vtt

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06. Pull Vs Fetch-kxXdk2HcOBo.mp4

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06. Pull vs Fetch.html

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07. Lesson Wrap Up-6Koa4nAu-04.ar.vtt

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07. Lesson Wrap Up-6Koa4nAu-04.mp4

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07. Lesson Wrap Up.html

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index.html

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/img/

ud456-l1-02-local-and-remote-repos.png

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ud456-l1-04-commit-count-local.png

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ud456-l1-04-commit-count-remote.png

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ud456-l1-04-git-pull.png

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ud456-l1-git-remote-add-terminal.png

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ud456-l1-github-create-repo-page.png

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ud456-l1-github-homepage-new-repo-button.png

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ud456-l1-github-homepage.png

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ud456-l1-project-commits.png

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/Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/

01. Intro-VkqtlJuZ9rs.ar.vtt

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01. Intro-VkqtlJuZ9rs.en.vtt

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01. Intro-VkqtlJuZ9rs.mp4

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01. Intro-VkqtlJuZ9rs.pt-BR.vtt

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01. Intro-VkqtlJuZ9rs.zh-CN.vtt

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01. Intro.html

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02. Forking A Repository.html

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02. Forking a Repository - What Is Forking-z4mkVwqVztc.ar.vtt

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02. Forking a Repository - What Is Forking-z4mkVwqVztc.en.vtt

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02. Forking a Repository - What Is Forking-z4mkVwqVztc.mp4

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02. Forking a Repository - What Is Forking-z4mkVwqVztc.zh-CN.vtt

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02. L2 - Pushing To A Fork-WRgNpr19t48.ar.vtt

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02. L2 - Pushing To A Fork-WRgNpr19t48.en.vtt

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02. L2 - Pushing To A Fork-WRgNpr19t48.mp4

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03. Reviewing Existing Work.html

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04. Determining What To Work On.html

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index.html

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/img/

ud456-l2-02-clone-linked-to-fork.png

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ud456-l2-02-git-fork-error.png

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ud456-l2-03-clone-lighthouse-project.png

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ud456-l2-03-commit-with-description.png

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ud456-l2-03-git-log-author.png

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ud456-l2-03-git-shortlog-flags.png

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ud456-l2-03-git-shortlog.png

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ud456-l2-04-issue-comments.png

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ud456-l2-04-lighthouse-issues.png

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ud456-l2-04-new-issue-button.png

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ud456-l2-04-sign-contributor-license.png

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ud456-l2-04-submit-new-issue.png

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/Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/

01. Intro-j5RmK0UHOTY.ar.vtt

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01. Intro-j5RmK0UHOTY.en.vtt

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01. Intro-j5RmK0UHOTY.mp4

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01. Intro-j5RmK0UHOTY.zh-CN.vtt

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01. Intro.html

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02. Create a Pull Request.html

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02. L3 - Pull Request In Action-d3AGtKmHxUk.ar.vtt

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02. L3 - Pull Request In Action-d3AGtKmHxUk.en.vtt

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02. L3 - Pull Request In Action-d3AGtKmHxUk.mp4

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02. L3 - Pull Request In Theory-twLr9ndsf90.ar.vtt

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02. L3 - Pull Request In Theory-twLr9ndsf90.mp4

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03. L3 - Include Upstream Changes-VvoC6hN6FjU.ar.vtt

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03. Stay in sync with source project.html

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04. Manage an active PR.html

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05. L3 - Squashing In Action-cL6ehKtJLUM.ar.vtt

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05. L3 - Squashing In Action-cL6ehKtJLUM.en.vtt

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05. L3 - Squashing In Action-cL6ehKtJLUM.mp4

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05. L3 - Squashing Introduction-mRbeT2XVL9w.ar.vtt

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05. L3 - Squashing Introduction-mRbeT2XVL9w.mp4

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05. Squash Commits.html

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06. Course Wrap Up-66Ut8Bv6kgc.ar.vtt

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06. Course Wrap Up-66Ut8Bv6kgc.mp4

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06. Course Wrap Up.html

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index.html

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/img/

ud456-l3-03-add-upstream-remote.png

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ud456-l3-03-fetch-upstream-changes.png

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ud456-l3-03-git-log-of-upstream-changes.png

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ud456-l3-03-git-remotes-origin.png

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ud456-l3-03-rename-repos.png

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ud456-l3-03-starred-repos.png

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ud456-l3-04-pull-request-comment.png

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/Part 11-Module 01-Lesson 01_Introduction/

01. Our Goal .html

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02. Instructors.html

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03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.en.vtt

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03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.mp4

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03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.pt-BR.vtt

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03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.zh-CN.vtt

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03. Essence of Linear Algebra.html

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04. Structure of this lesson.html

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05. Working with Equations.html

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06. Try our workspace out!.html

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07. Try our workspace again!.html

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index.html

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/img/

cp1a9390.jpg

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grant.png

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img-4646.jpg

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/Part 11-Module 01-Lesson 02_Vectors/

01. Vectors 1-oPBz-MLVUHk.en.vtt

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01. Vectors 1-oPBz-MLVUHk.mp4

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01. Vectors 1-oPBz-MLVUHk.pt-BR.vtt

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01. What's a Vector.html

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02. Vectors 2-R7WiQYixvRQ.en.vtt

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02. Vectors 2-R7WiQYixvRQ.mp4

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02. Vectors, what even are they Part 2.html

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03. Vectors 3-mWV_MpEjz9c.mp4

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03. Vectors, what even are they Part 3.html

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04. Vectors- Mathematical definition .html

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05. Transpose.html

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06. Magnitude and Direction .html

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07. Vectors- Quiz 1.html

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08. Operations in the Field.html

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09. Vector Addition.html

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10. Vectors- Quiz 2.html

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11. Scalar by Vector Multiplication.html

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12. Vectors Quiz 3.html

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13. Vectors Quiz Answers.html

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index.html

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/img/

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/Part 11-Module 01-Lesson 03_Linear Combination/

01. Linear Combination. Part 1.html

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01. Linear Combinations 1-fmal7UE7dEE.en.vtt

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01. Linear Combinations 1-fmal7UE7dEE.mp4

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01. Linear Combinations 1-fmal7UE7dEE.pt-BR.vtt

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02. Linear Combination. Part 2.html

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02. Linear Combinations 2-RsKJNDTb8nw.en.vtt

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02. Linear Combinations 2-RsKJNDTb8nw.mp4

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03. Linear Combination and Span.html

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04. Linear Combination -Quiz 1.html

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05. Linear Dependency .html

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06. Solving a Simplified Set of Equations.html

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07. Linear Combination - Quiz 2.html

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08. Linear Combination - Quiz 3.html

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index.html

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/img/

screen-shot-2018-01-26-at-10.16.48-pm.png

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/Part 11-Module 01-Lesson 04_Linear Transformation and Matrices/

01. What is a Matrix.html

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02. Matrix Addition.html

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03. Matrix Addition Quiz.html

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04. Scalar Multiplication of Matrix and Quiz.html

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05. Multiplication of a Square Matrices.html

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06. Square Matrix Multiplication Quiz.html

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07. Matrix Multiplication - General.html

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08. Matrix Multiplication Quiz.html

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09. Linear Transformation and Matrices . Part 1.html

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09. Linear Transformations 1-99jYIxBRDww.en.vtt

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09. Linear Transformations 1-99jYIxBRDww.mp4

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09. Linear Transformations 1-99jYIxBRDww.pt-BR.vtt

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09. Linear Transformations 1-99jYIxBRDww.zh-CN.vtt

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10. Linear Transformation and Matrices. Part 2.html

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10. Linear Transformations 2-imtEd8M6__s.en.vtt

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10. Linear Transformations 2-imtEd8M6__s.mp4

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10. Linear Transformations 2-imtEd8M6__s.zh-CN.vtt

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11. Linear Transformation and Matrices. Part 3.html

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11. Linear Transformations 3-g_yTyRwMzXU.en.vtt

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11. Linear Transformations 3-g_yTyRwMzXU.mp4

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12. Linear Transformation Quiz Answers.html

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index.html

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/img/

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/Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/

01. Introduce Instructors.html

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01. Instructors Introduction-lIvm8urf4GE.ar.vtt

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01. Instructors Introduction-lIvm8urf4GE.mp4

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01. Instructors Introduction-lIvm8urf4GE.zh-CN.vtt

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02. Text Optional Lessons Note.html

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03. Video Welcome!.html

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03. What Is Coming Up-oDJsnQcCPr4.ar.vtt

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03. What Is Coming Up-oDJsnQcCPr4.mp4

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04. Video What is Data Why is it important.html

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04. What is Data-ldTDAjrVsA8.ar.vtt

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04. What is Data-ldTDAjrVsA8.mp4

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05. Data Types-gT6EYlsLZkE.ar.vtt

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05. Video Data Types (Quantitative vs. Categorical).html

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06. Quiz Data Types (Quantitative vs. Categorical).html

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07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.ar.vtt

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07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.mp4

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07. Video Data Types (Ordinal vs. Nominal).html

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08. Continuous vs. Discrete Data-BzgZebZD9kk.ar.vtt

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08. Continuous vs. Discrete Data-BzgZebZD9kk.en.vtt

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08. Continuous vs. Discrete Data-BzgZebZD9kk.mp4

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08. Video Data Types (Continuous vs. Discrete).html

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09. Data Types Summary-T-KrQoAJUpI.ar.vtt

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09. Data Types Summary-T-KrQoAJUpI.mp4

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09. Video Data Types Summary.html

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10. Text + Quiz Data Types (Ordinal vs. Nominal).html

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11. Data Types (Continuous vs. Discrete).html

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12. Introduction to Summary Statistics-PCZmHCrcMcw.ar.vtt

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12. Introduction to Summary Statistics-PCZmHCrcMcw.mp4

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12. Video Introduction to Summary Statistics.html

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13. Calculating the Mean-1nzZxmJ8xvU.ar.vtt

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13. Calculating the Mean-1nzZxmJ8xvU.en.vtt

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13. Calculating the Mean-1nzZxmJ8xvU.mp4

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13. Video Measures of Center (Mean).html

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14. Measures of Center (Mean).html

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15. The Median-WlT3eeW0rb0.ar.vtt

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15. The Median-WlT3eeW0rb0.mp4

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15. Video Measures of Center (Median).html

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/Part 12-Module 01-Lesson 02_Descriptive Statistics - Part II/

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/Part 12-Module 01-Lesson 03_Admissions Case Study/

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11. Dangers Of Statistics-UYZXqP562qg.ar.vtt

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11. Dangers of Statistics.html

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12. Text Recap + Next Steps.html

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13. Case Study in Python.html

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index.html

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/Part 12-Module 01-Lesson 04_Probability/

01. Introduction to Probability-HeoQccoqfTk.ar.vtt

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15. One Of Three 1.html

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16. One Of Three 2.html

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17. Even Roll-DrnAR4SqlEE.ar.vtt

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17. Even Roll-DrnAR4SqlEE.mp4

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17. Even Roll-M3L0a5V4Nf0.ar.vtt

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17. Even Roll-M3L0a5V4Nf0.mp4

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17. Even Roll-M3L0a5V4Nf0.zh-CN.vtt

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17. Even Roll.html

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18. Doubles-On_Guw8wac8.ar.vtt

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18. Doubles-On_Guw8wac8.mp4

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18. Doubles-fkUyTJNbdzU.mp4

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18. Doubles.html

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19. Probability Conclusion-dsVKoXymYDU.ar.vtt

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19. Probability Conclusion-dsVKoXymYDU.mp4

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19. Probability Conclusion.html

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20. Text Recap + Next Steps.html

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index.html

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/img/

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/Part 12-Module 01-Lesson 05_Binomial Distribution/

01. Binomial-3koDdc9r73E.ar.vtt

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01. Binomial.html

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02. Heads Tails-iyX0-eXStbw.ar.vtt

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02. Heads Tails-yo55zJtJQwo.mp4

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02. Heads Tails.html

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08. Formula-DTdS-LlMTQ0.ar.vtt

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08. Formula-DTdS-LlMTQ0.mp4

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08. Formula-yTr8zCHdo5M.ar.vtt

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08. Formula.html

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09. Arrangements-GeINbOOYkF8.ar.vtt

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09. Arrangements-GeINbOOYkF8.mp4

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09. Arrangements-NRPcnpmFCg8.mp4

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09. Arrangements.html

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10. Binomial 1-07vOaYwecII.ar.vtt

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10. Binomial 1-07vOaYwecII.mp4

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10. Binomial 1-RBfFHxEjsIU.mp4

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10. Binomial 1-RBfFHxEjsIU.pt-BR.vtt

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10. Binomial 1.html

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11. Binomial 2-Uy7b3aMPnEY.ar.vtt

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11. Binomial 2.html

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12. Binomial 3-Jp2xJOtNQZ0.ar.vtt

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17. Text Recap + Next Steps.html

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/Part 12-Module 01-Lesson 06_Conditional Probability/

01. Introduction to Conditional Probability-Ok8948Wcbmo.ar.vtt

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10. Total Probability-YSYpzFR4k1I.ar.vtt

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index.html

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/Part 12-Module 01-Lesson 07_Bayes Rule/

01. Bayes Rule.html

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02. Cancer Test.html

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08. Bayes Rule Diagram-b8M9CWxRyQ4.ar.vtt

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28. Robot Sensing 8.html

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29. Generalizing-SdMk3aROgSc.ar.vtt

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29. Generalizing.html

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30. Sebastian At Home-R4zq6mPPMxs.ar.vtt

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30. Sebastian At Home.html

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31. Learning Objectives - Conditional Probability.html

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32. Reducing Uncertainty-zuFMhmKQ--o.ar.vtt

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32. Reducing Uncertainty.html

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33. Bayes' Rule and Robotics-meNSO42JF6I.ar.vtt

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33. Bayes' Rule and Robotics.html

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34. Learning from Sensor Data.html

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35. Using Sensor Data-vhl-SADfti8.ar.vtt

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35. Using Sensor Data.html

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36. Learning Objectives - Bayes' Rule.html

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37. Bayes Rule Conclusion-vlfDGCD8w0s.ar.vtt

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37. Bayes Rule Conclusion.html

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index.html

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/img/

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/Part 12-Module 01-Lesson 08_Python Probability Practice/

01. Introduction.html

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01. Python Probability Introduction-tFMdvAN7WDY.ar.vtt

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02. Simulating Coin Flips-7YtQNZ3iy6o.ar.vtt

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02. Simulating Coin Flips-7YtQNZ3iy6o.mp4

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02. Simulating Coin Flips.html

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03. Probability Quiz.html

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04. Simulating Many Coin Flips-AqpWQIj2V5Y.ar.vtt

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04. Simulating Many Coin Flips-AqpWQIj2V5Y.en.vtt

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04. Simulating Many Coin Flips-AqpWQIj2V5Y.mp4

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04. Simulating Many Coin Flips.html

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05. Binomial Distributions Quiz.html

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06. Cancer Test Results.html

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07. Conditional Probability Bayes Rule Quiz.html

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08. Conclusion.html

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08. Python Probability Conclusion-4JYar5GykXk.ar.vtt

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index.html

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/Part 12-Module 01-Lesson 09_Normal Distribution Theory/

01. Maximum Probability-5zkupL6EWh8.ar.vtt

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01. Maximum Probability-b2zvrFL8AUw.mp4

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08. Maximum.html

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10. Minimum.html

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11. Minimum Value.html

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12. Normalizer-mQ_IjrtmmAk.ar.vtt

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13. Formula Summary-zqo1RJEHT_0.ar.vtt

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14. Central Limit Theorem-36KLIHioAvA.ar.vtt

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14. Central Limit Theorem.html

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index.html

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/Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/

01. Introduction-SvdlBB-ZjcQ.ar.vtt

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01. Introduction-SvdlBB-ZjcQ.en.vtt

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01. Introduction-SvdlBB-ZjcQ.mp4

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01. Introduction-SvdlBB-ZjcQ.pt-BR.vtt

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01. Introduction.html

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02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.ar.vtt

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02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt

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02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4

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02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.pt-BR.vtt

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02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt

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02. Video Descriptive vs. Inferential Statistics.html

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03. Quiz Descriptive vs. Inferential (Udacity Students).html

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04. Quiz Descriptive vs. Inferential (Bagels).html

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05. Text Descriptive vs. Inferential Statistics.html

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06. Example of Sampling Distributions - Part I-1XezzP6kxUE.ar.vtt

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06. Example of Sampling Distributions - Part I-1XezzP6kxUE.zh-CN.vtt

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06. Video + Quiz Introduction to Sampling Distributions Part I.html

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07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.ar.vtt

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07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.mp4

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07. Video + Quiz Introduction to Sampling Distributions Part II.html

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08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.ar.vtt

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08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.mp4

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08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt

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08. Video Introduction to Sampling Distributions Part III.html

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09. Notebook + Quiz Sampling Distributions Python.html

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10. Text Sampling Distribution Notes.html

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11. Introduction To Notation-ISkBSUVH49M.ar.vtt

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11. Introduction To Notation-ISkBSUVH49M.en.vtt

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11. Introduction To Notation-ISkBSUVH49M.mp4

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11. Video Introduction to Notation.html

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12. Notation Parameters vs. Statistics-webref_dLrA.ar.vtt

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12. Notation Parameters vs. Statistics-webref_dLrA.en.vtt

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12. Notation Parameters vs. Statistics-webref_dLrA.mp4

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12. Notation Parameters vs. Statistics-webref_dLrA.pt-BR.vtt

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12. Video Notation for Parameters vs. Statistics.html

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13. Quiz Notation.html

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14. Other Sampling Distributions-Bxl0DonzX8c.ar.vtt

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14. Other Sampling Distributions-Bxl0DonzX8c.mp4

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14. Video Other Sampling Distributions.html

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15. Two Useful Theorems-jQ5i7CALdRQ.ar.vtt

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15. Two Useful Theorems-jQ5i7CALdRQ.en.vtt

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15. Two Useful Theorems-jQ5i7CALdRQ.mp4

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15. Two Useful Theorems-jQ5i7CALdRQ.pt-BR.vtt

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15. Two Useful Theorems-jQ5i7CALdRQ.zh-CN.vtt

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15. Video Two Useful Theorems - Law of Large Numbers.html

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16. Notebook + Quiz Law of Large Numbers.html

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17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.ar.vtt

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17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.en.vtt

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17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.mp4

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17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.pt-BR.vtt

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17. Video Two Useful Theorems - Central Limit Theorem.html

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18. Notebook + Quiz Central Limit Theorem.html

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19. Notebook + Quiz Central Limit Theorem - Part II.html

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20. Video When Does the Central Limit Theorem Not Work.html

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20. When Does the CLT Not Work-uZGTVUEMfrU.ar.vtt

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20. When Does the CLT Not Work-uZGTVUEMfrU.en.vtt

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20. When Does the CLT Not Work-uZGTVUEMfrU.mp4

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20. When Does the CLT Not Work-uZGTVUEMfrU.zh-CN.vtt

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21. Notebook + Quiz Central Limit Theorem - Part III.html

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22. Bootstrapping-42j3YclcZ4Q.ar.vtt

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22. Video Bootstrapping.html

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23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.ar.vtt

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23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.mp4

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23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.zh-CN.vtt

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23. Video Bootstrapping The Central Limit Theorem.html

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24. Notebook + Quiz Bootstrapping.html

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25. Background Of Bootstrapping-6Vg5kGoDl7k.ar.vtt

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25. Background Of Bootstrapping-6Vg5kGoDl7k.en.vtt

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25. Background Of Bootstrapping-6Vg5kGoDl7k.mp4

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25. Background Of Bootstrapping-6Vg5kGoDl7k.zh-CN.vtt

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25. Video The Background of Bootstrapping.html

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26. Video Why are Sampling Distributions Important.html

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26. Why Are Sampling Distributions Important-aDFDOCJKoH0.ar.vtt

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26. Why Are Sampling Distributions Important-aDFDOCJKoH0.en.vtt

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26. Why Are Sampling Distributions Important-aDFDOCJKoH0.mp4

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26. Why Are Sampling Distributions Important-aDFDOCJKoH0.zh-CN.vtt

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27. Quiz + Text Recap Next Steps.html

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index.html

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/Part 12-Module 01-Lesson 11_Confidence Intervals/

01. Confidence Intervals Introduction-crleT4000ak.en.vtt

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01. Confidence Intervals Introduction-crleT4000ak.mp4

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01. Confidence Intervals Introduction-crleT4000ak.pt-BR.vtt

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01. Confidence Intervals Introduction-crleT4000ak.zh-CN.vtt

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01. Video Introduction.html

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02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.en.vtt

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02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.mp4

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02. Video From Sampling Distributions to Confidence Intervals.html

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03. Sampling Distributions Confidence Intervals-gICzUhMVymo.en.vtt

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03. Sampling Distributions Confidence Intervals-gICzUhMVymo.mp4

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03. Sampling Distributions Confidence Intervals-gICzUhMVymo.zh-CN.vtt

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03. ScreenCast Sampling Distributions and Confidence Intervals.html

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04. Notebook + Quiz Building Confidence Intervals.html

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05. Confidence Interval for a Difference In Means-8hrWGzjyhck.en.vtt

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05. Confidence Interval for a Difference In Means-8hrWGzjyhck.mp4

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05. Confidence Interval for a Difference In Means-8hrWGzjyhck.zh-CN.vtt

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05. ScreenCast Difference In Means.html

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06. Notebook + Quiz Difference in Means.html

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07. Confidence Intervals Applications-C0wgmeRx9yE.en.vtt

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07. Confidence Intervals Applications-C0wgmeRx9yE.mp4

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07. Video Confidence Interval Applications.html

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08. Statistical vs. Practical Differences-RKHD1wzxxPA.en.vtt

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08. Statistical vs. Practical Differences-RKHD1wzxxPA.mp4

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08. Statistical vs. Practical Differences-RKHD1wzxxPA.pt-BR.vtt

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08. Video Statistical vs. Practical Significance.html

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09. Statistical vs. Practical Significance.html

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10. Traditional Confidence Interval Methods-DmZwYHuz2eM.en.vtt

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10. Traditional Confidence Interval Methods-DmZwYHuz2eM.mp4

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10. Video Traditional Confidence Intervals.html

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11. ScreenCast Traditional Confidence Interval Methods.html

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11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.en.vtt

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11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.mp4

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11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.pt-BR.vtt

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11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.zh-CN.vtt

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12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.en.vtt

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12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.mp4

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12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.pt-BR.vtt

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12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.zh-CN.vtt

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12. Video Other Language Associated with Confidence Intervals.html

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13. Other Language Associated with Confidence Intervals.html

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14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.en.vtt

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16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.en.vtt

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16. Video Confidence Intervals Hypothesis Tests.html

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17. Text Recap + Next Steps.html

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index.html

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/img/

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/Part 12-Module 01-Lesson 12_Hypothesis Testing/

01. Hypothesis Testing Introduction-Qi6F2rJAmrA.en.vtt

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01. Hypothesis Testing Introduction-Qi6F2rJAmrA.mp4

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01. Introduction.html

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02. Hypothesis Testing-9GbHHpiK6wk.en.vtt

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02. Hypothesis Testing-9GbHHpiK6wk.mp4

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02. Hypothesis Testing-9GbHHpiK6wk.pt-BR.vtt

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02. Hypothesis Testing.html

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03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.en.vtt

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03. Setting Up Hypothesis Tests - Part I.html

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04. Setting Up Hypotheses - Part II-nByvHz77GiA.en.vtt

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04. Setting Up Hypothesis Tests - Part II.html

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05. Quiz Setting Up Hypothesis Tests.html

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06. Types Of Errors - Part I-aw6GMxIvENc.en.vtt

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06. Types Of Errors - Part I-aw6GMxIvENc.mp4

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06. Types of Errors - Part I.html

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07. Quiz Types of Errors - Part I.html

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08. Types Of Errors - Part II-mbdSQ5CjdFs.en.vtt

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08. Types of Errors - Part II.html

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09. Quiz Types of Errors - Part II.html

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10. Types Of Errors - Part III-Z-srkCPsdaM.en.vtt

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10. Types Of Errors - Part III-Z-srkCPsdaM.mp4

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10. Types of Errors - Part III.html

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11. Quiz Types of Errors - Part III.html

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12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.en.vtt

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12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.mp4

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12. Common Types of Hypothesis Tests-8hv8KnvQ6JY.zh-CN.vtt

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12. Common Types of Hypothesis Tests.html

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13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.en.vtt

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13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.mp4

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13. How Do We Choose Between Hypotheses-JkXTwS-5Daw.pt-BR.vtt

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13. How Do We Choose Between Hypotheses.html

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13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.en.vtt

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13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.mp4

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13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.pt-BR.vtt

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13. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.zh-CN.vtt

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14. Simulating From the Null-sL2yJtHZd8Y.en.vtt

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14. Simulating From the Null-sL2yJtHZd8Y.mp4

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14. Video Simulating from the Null.html

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15. Notebook + Quiz Simulating from the Null.html

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16. What Is A P-value Anyway-eU6pUZjqviA.en.vtt

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16. What Is A P-value Anyway-eU6pUZjqviA.mp4

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16. What Is A P-value Anyway-eU6pUZjqviA.pt-BR.vtt

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16. What Is A P-value Anyway-eU6pUZjqviA.zh-CN.vtt

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16. What is a p-value Anyway.html

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17. Calculating the p-value-_W3Jg7jQ8jI.en.vtt

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17. Calculating the p-value-_W3Jg7jQ8jI.zh-CN.vtt

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17. Video Calculating the p-value.html

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18. Quiz What is a p-value Anyway.html

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19. Quiz Calculating a p-value.html

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20. Connecting Errors and P-Values-hFNjd5l9CLs.en.vtt

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20. Connecting Errors and P-Values-hFNjd5l9CLs.mp4

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20. Connecting Errors and P-Values-hFNjd5l9CLs.pt-BR.vtt

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20. Connecting Errors and P-Values.html

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21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.en.vtt

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21. Conclusions In Hypothesis Testing-I0Mo7hcxahY.mp4

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21. Conclusions in Hypothesis Testing.html

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22. Quiz Connecting Errors and P-Values.html

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23. Notebook + Quiz Drawing Conclusions.html

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24. Other Things to Consider - What if Our Sample is Large.html

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24. What If Our Sample Is Large-WoTCeSTL1eM.en.vtt

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24. What If Our Sample Is Large-WoTCeSTL1eM.mp4

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24. What If Our Sample Is Large-WoTCeSTL1eM.zh-CN.vtt

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25. Multiple Testing Corrections-DuMgeHrkIF0.en.vtt

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25. Multiple Testing Corrections-DuMgeHrkIF0.mp4

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25. Other Things to Consider - What if Test More Than Once.html

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26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.en.vtt

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26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.mp4

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26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.pt-BR.vtt

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26. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.zh-CN.vtt

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26. Other Things to Consider - How Do CIs and HTs Compare.html

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27. Notebook + Quiz Other Things to Consider.html

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28. Notebook + Quiz Other Things to Consider.html

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29. Hypothesis Testing Conclusion-nQFchD4XPPs.en.vtt

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29. Hypothesis Testing Conclusion-nQFchD4XPPs.mp4

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29. Hypothesis Testing Conclusion.html

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30. Quiz + Text Recap.html

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index.html

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/img/

screen-shot-2017-11-07-at-2.16.14-pm.png

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screen-shot-2017-11-07-at-2.17.08-pm.png

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/Part 12-Module 01-Lesson 13_Case Study AB tests/

01. Case Study Introduction-J5uvdPxHIfs.en.vtt

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01. Case Study Introduction-J5uvdPxHIfs.mp4

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01. Introduction.html

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02. AB Testing-EcWvhbIjT9o.en.vtt

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02. AB Testing-EcWvhbIjT9o.mp4

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02. AB Testing-EcWvhbIjT9o.pt-BR.vtt

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02. AB Testing.html

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03. AB Testing.html

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04. Business Example-Wzz7omSDfEk.en.vtt

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04. Business Example-Wzz7omSDfEk.mp4

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04. Business Example.html

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05. Experiment I-JLKAdT2JESk.en.vtt

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05. Experiment I-JLKAdT2JESk.mp4

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05. Experiment I-JLKAdT2JESk.pt-BR.vtt

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05. Experiment I.html

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06. Quiz Experiment I.html

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07. Metric - Click Through Rate-EpfoKAwV_Eg.en.vtt

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07. Metric - Click Through Rate-EpfoKAwV_Eg.mp4

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07. Metric - Click Through Rate.html

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08. Click Through Rate.html

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09. Experiment II-fq4eO7CybA4.en.vtt

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09. Experiment II.html

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10. Metric - Enrollment Rate.html

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11. Metric - Average Reading Duration-w6Y9ZxHDEbw.en.vtt

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11. Metric - Average Reading Duration-w6Y9ZxHDEbw.mp4

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11. Metric - Average Reading Duration-w6Y9ZxHDEbw.pt-BR.vtt

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11. Metric - Average Reading Duration-w6Y9ZxHDEbw.zh-CN.vtt

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11. Metric - Average Reading Duration.html

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12. Metric - Average Classroom Time.html

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13. Metric - Completion Rate.html

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14. Analyzing Multiple Metrics-DtZghKNa7Ak.en.vtt

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14. Analyzing Multiple Metrics-DtZghKNa7Ak.mp4

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14. Analyzing Multiple Metrics-DtZghKNa7Ak.pt-BR.vtt

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14. Analyzing Multiple Metrics-DtZghKNa7Ak.zh-CN.vtt

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14. Analyzing Multiple Metrics.html

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15. Quiz Analyzing Multiple Metrics.html

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16. Drawing Conclusions-s-4ghG9vrGQ.en.vtt

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16. Drawing Conclusions-s-4ghG9vrGQ.mp4

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16. Drawing Conclusions.html

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17. Quiz Difficulties in AB Testing.html

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18. Conclusion-qmGjRpMVBz8.en.vtt

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18. Conclusion-qmGjRpMVBz8.mp4

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18. Conclusion-qmGjRpMVBz8.pt-BR.vtt

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18. Conclusion.html

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index.html

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/Part 12-Module 01-Lesson 14_Regression/

01. Regression Introduction-PKqSS0TzXeA.en.vtt

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01. Regression Introduction-PKqSS0TzXeA.mp4

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01. Video Introduction.html

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02. Introduction to Machine Learning-pLcFPPI1L-0.en.vtt

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02. Introduction to Machine Learning-pLcFPPI1L-0.mp4

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02. Introduction to Machine Learning-pLcFPPI1L-0.pt-BR.vtt

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02. Introduction to Machine Learning-pLcFPPI1L-0.zh-CN.vtt

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02. Video Introduction to Machine Learning.html

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03. Quiz Machine Learning Big Picture.html

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04. Introduction to Linear Regression-RD4zbBvXDnM.en.vtt

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04. Introduction to Linear Regression-RD4zbBvXDnM.mp4

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04. Introduction to Linear Regression-RD4zbBvXDnM.pt-BR.vtt

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04. Video Introduction to Linear Regression.html

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05. Quiz Linear Regression Language.html

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06. Scatter Plots -DvlxZ37O4i8.ar.vtt

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06. Scatter Plots -DvlxZ37O4i8.en.vtt

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06. Scatter Plots -DvlxZ37O4i8.zh-CN.vtt

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06. Scatter Plots.html

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07. Quizzes On Scatter Plots.html

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08. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt

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08. Correlation Coefficients-rL5Bn8Fi-zE.en.vtt

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08. Correlation Coefficients-rL5Bn8Fi-zE.mp4

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08. Correlation Coefficients.html

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09. Correlation Coefficient Quizzes.html

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10. Video What Defines A Line.html

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10. What Defines A Line-lTqwhsSNP2c.en.vtt

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10. What Defines A Line-lTqwhsSNP2c.mp4

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10. What Defines A Line-lTqwhsSNP2c.pt-BR.vtt

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11. Quiz What Defines A Line - Notation Quiz.html

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12. Quiz What Defines A Line - Line Basics Quiz.html

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13. Fitting A Regression Line-xQob80zrT3s.en.vtt

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13. Fitting A Regression Line-xQob80zrT3s.mp4

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13. Fitting A Regression Line-xQob80zrT3s.pt-BR.vtt

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13. Fitting A Regression Line-xQob80zrT3s.zh-CN.vtt

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13. Video Fitting A Regression Line.html

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14. Text The Regression Closed Form Solution.html

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15. Fitting A Regression Line In Python-0CiMDbEUeS4.en.vtt

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15. Fitting A Regression Line In Python-0CiMDbEUeS4.mp4

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15. Fitting A Regression Line In Python-0CiMDbEUeS4.pt-BR.vtt

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15. Fitting A Regression Line In Python-0CiMDbEUeS4.zh-CN.vtt

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15. Screencast Fitting A Regression Line in Python.html

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16. How Do We Interpret Results-eLk0XGGMaCE.en.vtt

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16. How Do We Interpret Results-eLk0XGGMaCE.mp4

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16. How Do We Interpret Results-eLk0XGGMaCE.zh-CN.vtt

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16. Video How to Interpret the Results.html

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17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.en.vtt

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17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.mp4

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17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.pt-BR.vtt

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17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.zh-CN.vtt

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17. Video Does the Line Fit the Data Well.html

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18. Notebook + Quiz How to Interpret the Results.html

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19. Notebook + Quiz Regression - Your Turn - Part I.html

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20. Notebook + Quiz Your Turn - Part II.html

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21. Recap-DzMi27LI5l4.en.vtt

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21. Recap-DzMi27LI5l4.mp4

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21. Recap-DzMi27LI5l4.pt-BR.vtt

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/Part 12-Module 01-Lesson 15_Multiple Linear Regression/

01. Introduction to Multiple Linear Regression-b26v8HK-8-o.en.vtt

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01. Introduction to Multiple Linear Regression-b26v8HK-8-o.mp4

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01. Video Introduction.html

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02. Multiple Linear Regression-rvYZp99nj6c.en.vtt

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02. Multiple Linear Regression-rvYZp99nj6c.mp4

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02. Multiple Linear Regression-rvYZp99nj6c.pt-BR.vtt

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02. Video Multiple Linear Regression.html

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03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.en.vtt

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03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.mp4

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03. Screencast Fitting A Multiple Linear Regression Model.html

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04. Notebook + Quiz Fitting A MLR Model.html

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05. How Does MLR Work-bvM6eUYyurA.en.vtt

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06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.en.vtt

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06. Video Multiple Linear Regression Model Results.html

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08. Dummy Variables--QTgDd-fZuA.en.vtt

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11. Screencast Dummy Variables.html

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14. [Optional] Notebook + Quiz Other Encodings.html

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17. Multicollinearity VIFs-wbtrXMusDe8.en.vtt

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/Part 12-Module 01-Lesson 16_Logistic Regression/

01. Introduction to Logistic Regression-P_f2RjjnPEg.en.vtt

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04. Fitting Logistic Regression In Python-baQf-XiZQQ4.en.vtt

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18. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt

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/Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/

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03. Build A Recommendation Engine IBM-A0rVwTbntf4.en.vtt

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03. Introduction to Blogging for Data Science-WrvGpRN5XQI.en.vtt

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/Part 13-Module 01-Lesson 02_The Skills That Set You Apart/

01. What Do Data Scientists Do-sN2DbIJUZmw.en.vtt

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01. What do Data Scientists Do.html

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02. Interview Robert Chang [AirBnB].html

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04. Interview Dan [Coinbase].html

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/Part 14-Module 01-Lesson 01_The Data Science Process/

01. Introduction-VpxATYHhKM8.en.vtt

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19. The Data Science Process Modeling-bzR6HQBn5CA.en.vtt

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20. Predicting Salary-g1ZAn02ETK4.en.vtt

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43. Screencast + Notebook Putting It All Together Solution.html

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44. Text + Quiz Results.html

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45. The Data Science Process Evaluate And Deploy-sxT43JlH_eM.en.vtt

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/Part 14-Module 01-Lesson 02_Communicating to Stakeholders/

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/Part 14-Module 01-Lesson 03_Project Write A Data Science Blog Post/

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/Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/

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17. Next Steps.html

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/Part 15-Module 01-Lesson 01_Introduction to Software Engineering/

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index.html

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/Part 15-Module 01-Lesson 02_Software Engineering Practices Pt I/

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02. Clean and Modular Code.html

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/Part 15-Module 01-Lesson 03_Software Engineering Practices Pt II/

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13. Tips for Conducting a Code Review.html

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index.html

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/Part 15-Module 01-Lesson 04_Introduction to Object-Oriented Programming/

01. Introduction-5DfFaAl1Wmc.en.vtt

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01. Introduction.html

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02. L3 02 Proced Vs OOP V1 V3-psXD_J8FnCQ.en.vtt

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02. Procedural vs. Object-Oriented Programming.html

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03. Class, Object, Method and Attribute.html

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16. Inheritance Probability Distribution.html

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17. Demo Inheritance Probability Distributions.html

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18. Advanced OOP Topics.html

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19. Organizing Code Into Modules-AARS10U5bbo.en.vtt

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20. Demo Modularized Code.html

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21. 15 Making a Package v2-Hj2OBr1CGZM.en.vtt

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27. Putting Code on PyPi.html

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28. Exercise Upload to PyPi.html

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29. L3 21 Outro v1 V2-DStO1hBKtHQ.en.vtt

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29. Lesson Summary.html

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index.html

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/img/

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/Part 15-Module 01-Lesson 05_Portfolio Exercise Upload a Package to PyPi/

01. Introduction.html

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02. Troubleshooting Possible Errors.html

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03. Workspace.html

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index.html

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/Part 15-Module 01-Lesson 06_Web Development/

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03. Components of a Web App.html

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14. Bootstrap Library-KsrqjguHWUI.en.vtt

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14. Bootstrap Library-KsrqjguHWUI.mp4

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14. Bootstrap Library.html

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16. 18 Screencast Plotly V2-QsmOW1jNeio.mp4

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16. Plotly.html

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20. Flask.html

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25. 40 Screencast Flask Pandas Plotly Part2 V2-yx-DRzMsblI.en.vtt

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29. Exercise Flask + Plotly + Pandas.html

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30. Deployment-YPfNzpnm_Rk.en.vtt

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30. Deployment-YPfNzpnm_Rk.pt-BR.vtt

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30. Deployment.html

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index.html

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/Part 15-Module 01-Lesson 07_Portfolio Exercise Deploy a Data Dashboard/

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02. Workspace Portfolio Exercise.html

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03. Troubleshooting Possible Errors.html

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04. Congratulations.html

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index.html

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/Part 16-Module 01-Lesson 01_Introduction to Data Engineering/

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02. Roles Of A Data Engineer-f57UbUlSDgo.en.vtt

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/Part 16-Module 01-Lesson 02_ETL Pipelines/

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01. Introduction.html

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03. World Bank Datasets-lNPzOLzZVbw.en.vtt

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04. How to Tackle the Exercises.html

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18. Matching Encodings-398xRMnhjGk.en.vtt

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20. 28 Missing Data Causes V1 V2-zlw8ESS6Q88.en.vtt

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24. SQL, optimization, and ETL - Robert Chang Airbnb.html

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33. Data Engineering Importance-VO-OrJ0JqxM.en.vtt

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37. Exercise Feature Engineering.html

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38. Bloopers.html

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39. 47 Load V1 V1-Us1hWDaabxo.en.vtt

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39. Load.html

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40. Exercise Load.html

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41. 52 Putting It All Together V1 1 V1-D2Th0KdPI-Y.en.vtt

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42. Exercise Putting It All Together.html

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43. Lesson Summary.html

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43. Outro V1 V4-XE3aoYOXeBw.en.vtt

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index.html

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/Part 16-Module 01-Lesson 03_NLP Pipelines/

01. NLP and Pipelines.html

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01. Natural Language Processing-UQBxJzoCp-I.en.vtt

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01. Natural Language Processing-UQBxJzoCp-I.mp4

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01. Natural Language Processing-UQBxJzoCp-I.zh-CN.vtt

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02. How NLP Pipelines Work.html

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02. NLP M1-L1 01 NLP Pipeline-vJx6oKlu_MM.en.vtt

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02. NLP M1-L1 01 NLP Pipeline-vJx6oKlu_MM.mp4

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02. NLP M1-L1 01 NLP Pipeline-vJx6oKlu_MM.zh-CN.vtt

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03. Text Processing-6LO6I5M18PQ.en.vtt

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03. Text Processing.html

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04. Cleaning-qawXp9DPV6I.en.vtt

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04. Cleaning.html

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06. Normalization-eOV2UUY8vtM.en.vtt

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08. Tokenization-4Ieotbeh4u8.en.vtt

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18. Feature Extraction-UgENzCmfFWE.en.vtt

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19. Bag Of Words-A7M1z8yLl0w.en.vtt

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20. 02 TF-IDF-LYYWIrWbBq4.en.vtt

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24. Modeling.html

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27. Embeddings For Deep Learning-gj8u1KG0H2w.en.vtt

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27. Embeddings For Deep Learning-gj8u1KG0H2w.mp4

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index.html

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/Part 16-Module 01-Lesson 04_Machine Learning Pipelines/

01. 01 Intro V1 V3-Zl_es7xtSqk.en.vtt

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01. 01 Intro V1 V3-Zl_es7xtSqk.mp4

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01. Introduction.html

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02. Corporate Messaging Case Study-xnDsUsrF884.en.vtt

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02. Corporate Messaging Case Study.html

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03. Case Study Clean and Tokenize.html

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04. Solution Clean and Tokenize.html

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05. Machine Learning Workflow-0nA6oTIlwaA.en.vtt

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05. Machine Learning Workflow.html

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06. Case Study Machine Learning Workflow.html

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07. Solution Machine Learning Workflow.html

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08. Using Pipeline.html

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08. Using Pipelines-mxFrS8qpZ6Y.en.vtt

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08. Using Pipelines-mxFrS8qpZ6Y.mp4

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09. 08 1 Advantages Of Using Pipeline V1 V2-ASYcx911E2Q.en.vtt

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09. Advantages of Using Pipeline.html

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10. Case Study Build Pipeline.html

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11. Solution Build Pipeline.html

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12. 12 Pipelines And Feature Unions V1 V3-zduxy0g23L0.en.vtt

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13. Using Feature Union.html

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13. Using Feature Unions-QmE6CMGar1U.mp4

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14. Case Study Add Feature Union.html

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15. Solution Add Feature Union.html

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16. Creating Custom Transformers-TBxUCQdXRjY.en.vtt

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16. Creating Custom Transformers-TBxUCQdXRjY.mp4

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16. Creating Custom Transformers.html

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17. Case Study Create Custom Transformer.html

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18. Solution Create Custom Transformer.html

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19. 15 Pipelines And Grid Search V1 V3-HZaOiSxJjCY.en.vtt

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19. 15 Pipelines And Grid Search V1 V3-HZaOiSxJjCY.mp4

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19. Pipelines and Grid Search.html

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20. Using Grid Search with Pipelines.html

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20. Using Grid Search-iTL43Jk9_bQ.en.vtt

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20. Using Grid Search-iTL43Jk9_bQ.mp4

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21. Case Study Grid Search Pipeline.html

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22. Solution Grid Search Pipeline.html

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23. 24 Conclusion V1 V2-Jq6pj_uKDmY.en.vtt

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23. Conclusion.html

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index.html

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/Part 16-Module 02-Lesson 01_Project Disaster Response Pipeline/

01. Figure 8 Project-QbLVh5GTuJQ.en.vtt

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01. Figure 8 Project-QbLVh5GTuJQ.mp4

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01. Figure 8 Project-QbLVh5GTuJQ.pt-BR.vtt

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01. Project Introduction.html

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02. Disaster Relief Project Preview-DuwYAjqGM3E.en.vtt

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02. Disaster Relief Project Preview-DuwYAjqGM3E.mp4

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02. Project Overview.html

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03. Project Details.html

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04. Project Workspace - ETL.html

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05. Project Workspace - ML Pipeline.html

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06. Project Workspace IDE.html

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Project Description - Disaster Response Pipelines.html

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index.html

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/img/

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disaster-response-project2.png

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/Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/

01. Get Opportunities with LinkedIn.html

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01. Why Network-exjEm9Paszk.ar.vtt

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01. Why Network-exjEm9Paszk.es-MX.vtt

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01. Why Network-exjEm9Paszk.mp4

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02. Meet Chris-0ccflD9x5WU.ar.vtt

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02. Meet Chris-0ccflD9x5WU.mp4

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02. Meet Chris-0ccflD9x5WU.pt-BR.vtt

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02. Use Your Story to Stand Out.html

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03. Elevator Pitch-S-nAHPrkQrQ.ar.vtt

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03. Elevator Pitch-S-nAHPrkQrQ.en.vtt

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03. Elevator Pitch-S-nAHPrkQrQ.mp4

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03. Why Use an Elevator Pitch.html

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04. Create Your Elevator Pitch.html

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05. Use Your Elevator Pitch on LinkedIn.html

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06. Create Your Profile With SEO In Mind.html

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07. Profile Essentials.html

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08. Work Experiences Accomplishments.html

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09. Build and Strengthen Your Network.html

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10. Reaching Out on LinkedIn.html

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11. Boost Your Visibility.html

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12. Up Next.html

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Project Description - Improve Your LinkedIn Profile.html

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Project Rubric - Improve Your LinkedIn Profile.html

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index.html

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/img/

profile-pics.jpg

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/Part 17-Module 01-Lesson 01_Intro to Experiment Design and Recommendation Engines/

01. C4 Intro-gXlqR86h0yI.en.vtt

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02. Course Syllabus.html

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03. Dan Frank Interview-Me-KRvZW1QQ.mp4

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03. Interview Dan [Coinbase].html

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04. Experimental Design Insights With Richard Sharp-XDBw2nfOrsU.en.vtt

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04. Experimental Design Insights With Richard Sharp-XDBw2nfOrsU.mp4

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04. Interview Richard [Starbucks].html

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index.html

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/Part 17-Module 02-Lesson 01_Concepts in Experiment Design/

01. Introduction-RVcFzwBXI2M.en.vtt

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01. Introduction-RVcFzwBXI2M.mp4

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01. Lesson Introduction.html

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02. What Is An Experiment Pt 2-PYzN1usi7QY.en.vtt

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02. What Is An Experiment-fH_xF5_SDCE.en.vtt

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02. What is an Experiment.html

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03. Types Of Experiments-7ihDj4M7EiU.en.vtt

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04. Types Of Sampling-GF_eQqNoarI.en.vtt

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04. Types of Sampling.html

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05. Measuring Outcomes Pt 1-HPmMEkbT2uE.en.vtt

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05. Measuring Outcomes Pt 1-HPmMEkbT2uE.mp4

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05. Measuring Outcomes Pt 2-yLdXcRXcfPw.en.vtt

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05. Measuring Outcomes Pt 2-yLdXcRXcfPw.mp4

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05. Measuring Outcomes.html

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06. Creating Metrics-__7tzDUY870.en.vtt

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06. Creating Metrics-__7tzDUY870.mp4

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06. Creating Metrics.html

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07. Controlling Variables-pLTneSg2MRY.en.vtt

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07. Controlling Variables.html

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08. Checking Validity-H3H1SZXqDmQ.en.vtt

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08. Checking Validity-H3H1SZXqDmQ.mp4

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09. Checking Bias-ppjNNY4DhPw.en.vtt

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09. Checking Bias-ppjNNY4DhPw.mp4

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09. Checking Bias.html

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10. Ethics In Experimentation Pt 2-0qcJ_oggdKw.en.vtt

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10. Ethics In Experimentation Pt 2-0qcJ_oggdKw.mp4

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10. Ethics In Experimentation Pt3-_HTolKktaC4.mp4

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10. Ethics in Experimentation.html

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11. A SMART Mnemonic for Experiment Design.html

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11. SMART Mnemonic-B0Bnxyu2aKM.en.vtt

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11. SMART Mnemonic-B0Bnxyu2aKM.mp4

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12. Conclusions-yMRRXDKb428.en.vtt

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12. Conclusions-yMRRXDKb428.mp4

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12. Conclusions-yMRRXDKb428.pt-BR.vtt

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12. Lesson Conclusion.html

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index.html

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/Part 17-Module 02-Lesson 02_Statistical Considerations in Testing/

01. Intro-EBGMcpWe8-U.en.vtt

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01. Intro-EBGMcpWe8-U.mp4

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01. Intro-EBGMcpWe8-U.pt-BR.vtt

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01. Lesson Introduction.html

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02. Practice Statistical Significance.html

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03. Statistical Significance - Solution.html

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04. Practical Significance-eJ3idt3AJ7E.en.vtt

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04. Practical Significance-eJ3idt3AJ7E.mp4

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04. Practical Significance-eJ3idt3AJ7E.pt-BR.vtt

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04. Practical Significance.html

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05. Experiment Size-sImRm8e01jA.en.vtt

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05. Experiment Size-sImRm8e01jA.mp4

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05. Experiment Size-sImRm8e01jA.pt-BR.vtt

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05. Experiment Size.html

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06. Experiment Size - Solution.html

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07. Using Dummy Tests-rURTLjh3Hlc.en.vtt

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07. Using Dummy Tests-rURTLjh3Hlc.mp4

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07. Using Dummy Tests-rURTLjh3Hlc.pt-BR.vtt

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07. Using Dummy Tests.html

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08. Non-Parametric Tests Part I.html

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09. Non-Parametric Tests Part I - Solution.html

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10. Non-Parametric Tests Part II.html

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11. Non-Parametric Tests Part II - Solution.html

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12. Analyzing Multiple Metrics Pt 1-SNFHYbJvlZU.en.vtt

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12. Analyzing Multiple Metrics Pt 1-SNFHYbJvlZU.mp4

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12. Analyzing Multiple Metrics Pt 2-x7foG7murvU.en.vtt

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12. Analyzing Multiple Metrics Pt 2-x7foG7murvU.mp4

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12. Analyzing Multiple Metrics.html

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13. Early Stopping-taIJZMNwRsI.en.vtt

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13. Early Stopping-taIJZMNwRsI.mp4

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13. Early Stopping.html

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14. Early Stopping - Solution.html

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15. Conclusions-3IFF1GzUq0Y.en.vtt

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15. Conclusions-3IFF1GzUq0Y.mp4

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15. Conclusions-3IFF1GzUq0Y.pt-BR.vtt

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15. Lesson Conclusion.html

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index.html

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/img/

c03-practicalsignificance-01.png

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c03-practicalsignificance-02.png

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c03-practicalsignificance-03.png

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c08-multimetrics-01.png

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/Part 17-Module 02-Lesson 03_AB Testing Case Study/

01. Intro-28mN6RvGXDM.en.vtt

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01. Intro-28mN6RvGXDM.mp4

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01. Intro-28mN6RvGXDM.pt-BR.vtt

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01. Lesson Introduction.html

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02. Scenario Description.html

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03. Building a Funnel.html

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04. Building a Funnel - Discussion.html

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05. Deciding on Metrics - Part I.html

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06. Deciding on Metrics - Part II.html

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07. Deciding on Metrics - Discussion.html

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08. Experiment Sizing.html

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09. Experiment Sizing - Discussion.html

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10. Validity, Bias, and Ethics - Discussion.html

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11. Analyze Data.html

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12. Draw Conclusions.html

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13. Draw Conclusions - Discussion.html

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14. Conclusion-2G6x3oQnjy4.en.vtt

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14. Conclusion-2G6x3oQnjy4.mp4

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14. Conclusion-2G6x3oQnjy4.pt-BR.vtt

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14. Lesson Conclusion.html

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index.html

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/Part 17-Module 02-Lesson 04_Portfolio Exercise Starbucks/

01. Introduction.html

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01. Starbucks Lab-QPKRboscAf4.en.vtt

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01. Starbucks Lab-QPKRboscAf4.mp4

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02. Overview.html

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03. Workspace.html

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index.html

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/media/

New-Starbucks-Logo-1200x969.jpg

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/Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/

01. Intro-svCesgAQ46Q.en.vtt

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01. Intro-svCesgAQ46Q.mp4

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01. Intro-svCesgAQ46Q.pt-BR.vtt

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01. Video Intro.html

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02. Identifying Recommendation Engines-KwegrgvV-V4.en.vtt

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02. Identifying Recommendation Engines-KwegrgvV-V4.mp4

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02. Video + Text Example Recommendation Engines.html

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03. Text What's Ahead.html

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04. Intro To MovieTweetings-cuXvLIkq_W8.en.vtt

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04. Intro To MovieTweetings-cuXvLIkq_W8.mp4

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05. Notebook MovieTweeting Data.html

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06. Recommendations 1 6 0950 V1-yrNZ0sQwNcs.en.vtt

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06. Recommendations 1 6 11123244 V1-QlILlYuWF9U.mp4

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06. Screencast Solution MovieTweeting Data .html

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07. Knowledge Based Recommendations-C_vU1tjQHZI.en.vtt

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07. Knowledge Based Recommendations-C_vU1tjQHZI.mp4

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07. Video Ways to Recommend Knowledge Based.html

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08. Notebook Knowledge Based.html

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09. Recommendations 1 9 03362 V1-MwRSg5RASoc.en.vtt

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09. Recommendations 1 9 03362 V1-MwRSg5RASoc.mp4

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09. Recommendations 1 9 33514421 V1-TCaeEdrbYRc.mp4

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09. Screencast Solution Knowledge Based.html

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10. More Personalized Recommendations-9l8mi7i6iW4.en.vtt

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10. More Personalized Recommendations-9l8mi7i6iW4.mp4

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10. Video More Personalized Recommendations.html

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11. Intro To Collab Filtering-wGq7dUgJpsc.en.vtt

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11. Intro To Collab Filtering-wGq7dUgJpsc.mp4

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11. Intro To Collab Filtering-wGq7dUgJpsc.pt-BR.vtt

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11. Video Ways to Recommend Collaborative Filtering.html

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12. Types Of Collaborative Filtering-fZhkWHHP6SM.en.vtt

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12. Types Of Collaborative Filtering-fZhkWHHP6SM.mp4

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12. Types Of Collaborative Filtering-fZhkWHHP6SM.pt-BR.vtt

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12. Video + Quiz Collaborative Filtering Content Based Recs.html

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13. Measuring SImilarity-G_Y6IPmp7Xs.en.vtt

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13. Measuring SImilarity-G_Y6IPmp7Xs.mp4

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13. Measuring SImilarity-G_Y6IPmp7Xs.pt-BR.vtt

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13. Video + Text Measuring Similarity.html

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14. Notebook Measuring Similarity.html

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15. Recommendations 1 14 012725 V1-Y1dN-mB39rM.en.vtt

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15. Recommendations 1 14 012725 V1-Y1dN-mB39rM.mp4

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15. Recommendations 1 14 10131720 V1-DWHYK0XSI70.mp4

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15. Recommendations 1 14 7251010 V1-sVZ5S1nnRf8.en.vtt

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15. Recommendations 1 14 7251010 V1-sVZ5S1nnRf8.mp4

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15. Screencast Solution Measuring Similarity.html

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16. Identifying Recommendations-P60qvS_OTMg.en.vtt

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16. Identifying Recommendations-P60qvS_OTMg.mp4

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16. Identifying Recommendations-P60qvS_OTMg.pt-BR.vtt

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16. Video Identifying Recommendations.html

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17. Notebook Collaborative Filtering.html

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18. Recommendations 1 17a 0422 V1-J4MOXJhMGGA.en.vtt

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18. Recommendations 1 17a 0422 V1-J4MOXJhMGGA.mp4

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18. Recommendations 1 17b 5451216 V1-lf2Q0AE5esk.mp4

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18. Screencast Solution Collaborative Filtering.html

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19. Recommendations 1 17b 20332637 V1-UnDocJ9VUec.en.vtt

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19. Recommendations 1 17b 20332637 V1-UnDocJ9VUec.mp4

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19. Recommendations 1 17b 26423140 V1-uNQHtPrfi4o.mp4

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19. Recommendations 1 17b 31423505 V1-A0uOjClDnW8.mp4

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19. Recommendations 1 17b 36044330 V1-b5gFe8Ij-g0.mp4

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19. Screencast Solutions for Collaborative Filtering.html

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20. Content Based Recommendations-pnGHpB77Mys.en.vtt

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20. Content Based Recommendations-pnGHpB77Mys.mp4

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20. Content Based Recommendations-pnGHpB77Mys.pt-BR.vtt

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20. Video Ways to Recommend Content Based.html

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21. Notebook Content Based.html

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22. Recommendations 1 20 0425 V1-vPpX7ITgb3g.en.vtt

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22. Recommendations 1 20 0425 V1-vPpX7ITgb3g.mp4

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22. Recommendations 1 20 10491855 V1-BafXxtTuZgQ.mp4

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22. Recommendations 1 20 10491855 V2-pjoxB00grHw.mp4

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22. Recommendations 1 20 4271048 V1-2On65U7Panw.en.vtt

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22. Recommendations 1 20 4271048 V1-2On65U7Panw.mp4

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22. Screencast Solution Content Based.html

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23. Types Of Recommendations-uoXF81AO21E.en.vtt

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23. Types Of Recommendations-uoXF81AO21E.mp4

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23. Types Of Recommendations-uoXF81AO21E.pt-BR.vtt

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23. Video Three Types of Recommendation Systems.html

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24. Text More Recommendation Technniques.html

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25. Quiz Recommendation Methods.html

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26. Types Of Ratings-fMjqe4sxBlQ.en.vtt

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26. Types Of Ratings-fMjqe4sxBlQ.mp4

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26. Video Types of Ratings.html

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27. Goals Of Recommendation Systems-WzelOlFeDmU.en.vtt

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27. Goals Of Recommendation Systems-WzelOlFeDmU.mp4

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27. Goals Of Recommendation Systems-WzelOlFeDmU.pt-BR.vtt

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27. Video Goals of Recommendation Systems.html

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28. Quiz Types of Ratings Goals of Recommendation Systems.html

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29. Conclusion-zX5jZH2y8d8.en.vtt

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29. Conclusion-zX5jZH2y8d8.mp4

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29. Conclusion-zX5jZH2y8d8.pt-BR.vtt

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29. Video Outro.html

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30. Text Recap.html

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index.html

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/img/

collage2.png

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screen-shot-2018-08-07-at-4.35.30-pm.png

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/Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/

01. Lesson Introduction-rw3YaQ2CTNQ.mp4

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01. Video Intro.html

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02. Text What's Ahead.html

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03. How Do We Know Our Recs Are Good-D0H_fjJ35CU.en.vtt

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03. How Do We Know Our Recs Are Good-D0H_fjJ35CU.mp4

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03. How Do We Know Our Recs Are Good-D0H_fjJ35CU.pt-BR.vtt

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03. Video How Do We Know Our Recommendations Are Good.html

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04. Text Validating Your Recommendations.html

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05. Quiz Regression Metrics.html

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06. Video Why SVD.html

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06. Why SVD-WdW1-rRQrLk.mp4

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07. Latent Factors-jZz7tFEF2Dc.en.vtt

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07. Latent Factors-jZz7tFEF2Dc.mp4

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08. Quiz Latent Factors.html

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09. SVD-t2XTuHq6-xc.en.vtt

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09. SVD-t2XTuHq6-xc.mp4

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09. Video Singular Value Decomposition.html

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10. Notebook SVD Practice.html

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11. Recommendations 2 10 0424 V1-x-End5px36M.en.vtt

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13. Text SVD Closed Form Solution.html

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14. 14 Funk SVD-H8gdwXy_npI.en.vtt

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14. 14 Funk SVD-H8gdwXy_npI.mp4

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14. Video FunkSVD.html

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16. Recommendations 2 16 1051320 V1-_4N6h82szWo.en.vtt

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17. Video FunkSVD Review.html

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18. Notebook How Are We Doing.html

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19. Screencast How Are We Doing.html

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20. The Cold Start Problem-DNz7aywJVzA.en.vtt

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20. The Cold Start Problem-DNz7aywJVzA.mp4

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24. Screencast Code Walkthrough.html

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25. Workspace Recommender Module.html

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26. Conclusion-R5-OYqKk9Ys.en.vtt

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26. Video Conclusion.html

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27. Text Review.html

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index.html

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/img/

screen-shot-2018-09-13-at-6.32.03-pm.png

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screen-shot-2018-09-14-at-10.11.13-am.png

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screen-shot-2018-09-14-at-10.16.10-am.png

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screen-shot-2018-09-14-at-2.25.01-pm.png

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/Part 17-Module 04-Lesson 01_Recommendation Engines/

01. IBM Project Overview-XP_f64c07Gc.en.vtt

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01. IBM Project Overview-XP_f64c07Gc.mp4

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01. IBM Project Overview-XP_f64c07Gc.pt-BR.vtt

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01. Project Introduction.html

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02. Project Details.html

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03. Project Workspace.html

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Project Description - Recommendations with IBM.html

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Project Rubric - Recommendations with IBM.html

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index.html

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/img/

screen-shot-2018-09-17-at-3.40.30-pm.png

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/Part 17-Module 05-Lesson 01_Upcoming Lesson/

01. Final Project Release.html

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index.html

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/img/

congrats.jpg

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/

[CourseClub.NET].url

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[DesireCourse.Com].url

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index.html

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/assets/css/

bootstrap.min.css

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jquery.mCustomScrollbar.min.css

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katex.min.css

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plyr.css

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styles.css

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/assets/css/fonts/

KaTeX_AMS-Regular.ttf

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KaTeX_AMS-Regular.woff

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KaTeX_AMS-Regular.woff2

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KaTeX_Caligraphic-Bold.ttf

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KaTeX_Caligraphic-Bold.woff

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KaTeX_Caligraphic-Bold.woff2

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KaTeX_Caligraphic-Regular.ttf

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KaTeX_Caligraphic-Regular.woff

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KaTeX_Caligraphic-Regular.woff2

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KaTeX_Fraktur-Bold.ttf

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KaTeX_Fraktur-Bold.woff

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KaTeX_Fraktur-Bold.woff2

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KaTeX_Fraktur-Regular.ttf

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KaTeX_Fraktur-Regular.woff

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KaTeX_Fraktur-Regular.woff2

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KaTeX_Main-Bold.ttf

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KaTeX_Main-Bold.woff

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KaTeX_Main-Bold.woff2

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KaTeX_Main-BoldItalic.ttf

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KaTeX_Main-BoldItalic.woff

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KaTeX_Main-BoldItalic.woff2

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KaTeX_Main-Italic.ttf

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KaTeX_Main-Italic.woff

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KaTeX_Main-Italic.woff2

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KaTeX_Main-Regular.ttf

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KaTeX_Main-Regular.woff

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KaTeX_Main-Regular.woff2

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KaTeX_Math-BoldItalic.ttf

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KaTeX_Math-BoldItalic.woff

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KaTeX_Math-BoldItalic.woff2

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KaTeX_Math-Italic.ttf

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KaTeX_Math-Italic.woff

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KaTeX_Math-Italic.woff2

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KaTeX_SansSerif-Bold.ttf

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KaTeX_SansSerif-Bold.woff

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KaTeX_SansSerif-Bold.woff2

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KaTeX_SansSerif-Italic.ttf

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KaTeX_SansSerif-Italic.woff

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KaTeX_SansSerif-Italic.woff2

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KaTeX_SansSerif-Regular.ttf

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KaTeX_SansSerif-Regular.woff

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KaTeX_SansSerif-Regular.woff2

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KaTeX_Script-Regular.ttf

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KaTeX_Script-Regular.woff

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KaTeX_Script-Regular.woff2

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KaTeX_Size1-Regular.ttf

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KaTeX_Size1-Regular.woff

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KaTeX_Size1-Regular.woff2

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KaTeX_Size2-Regular.ttf

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KaTeX_Size2-Regular.woff

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KaTeX_Size2-Regular.woff2

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KaTeX_Size3-Regular.ttf

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KaTeX_Size3-Regular.woff

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KaTeX_Size3-Regular.woff2

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KaTeX_Size4-Regular.ttf

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KaTeX_Size4-Regular.woff

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KaTeX_Size4-Regular.woff2

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KaTeX_Typewriter-Regular.ttf

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KaTeX_Typewriter-Regular.woff

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KaTeX_Typewriter-Regular.woff2

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/assets/img/

udacimak.png

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/assets/js/

bootstrap.min.js

51.0 KB

jquery-3.3.1.min.js

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jquery.mCustomScrollbar.concat.min.js

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katex.min.js

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plyr.polyfilled.min.js

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Total files 8307


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