TutNetFlix com Udemy Complete Machine Learning and Data Science Zero to Mastery |
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Name |
[TutNetFlix.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery |
DOWNLOAD Copy Link |
Total Size |
20.5 GB |
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Total Files |
815 |
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Hash |
E9EBE8CB28EB780549DBB4CCFD04455AA24F78FA |
/5. Data Science Environment Setup/ |
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/1. Introduction/ |
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/2. Machine Learning 101/ |
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/3. Machine Learning and Data Science Framework/ |
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3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html |
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/4. The 2 Paths/ |
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/6. Pandas Data Analysis/ |
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3.2 10-minutes to pandas (from the pandas documentation).html |
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3.3 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html |
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3.4 Introduction to Pandas Jupyter Notebook (with annotations).html |
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11.1 Introduction to Pandas Jupyter Notebook (from the videos).html |
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11.2 Introduction to Pandas Jupyter Notebook (with annotations).html |
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/7. NumPy/ |
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2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html |
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2.3 Introduction to NumPy Jupyter Notebook (with annotations).html |
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16.2 Introduction to NumPy Jupyter Notebook (from the videos).html |
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16.3 Introduction to NumPy Jupyter Notebook (with annotations).html |
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/8. Matplotlib + Seaborn Plotting and Data Visualization/ |
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2.2 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html |
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19.1 Introduction to Matplotlib Notebook (from the videos).html |
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/9. Scikit-learn Creating Machine Learning Models/ |
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2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html |
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2.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html |
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12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 |
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12. Getting Your Data Ready Handling Missing Values With Pandas.srt |
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13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 |
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13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt |
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14.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html |
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15. Choosing The Right Model For Your Data 2 (Regression).mp4 |
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15. Choosing The Right Model For Your Data 2 (Regression).srt |
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18. Choosing The Right Model For Your Data 3 (Classification).mp4 |
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18. Choosing The Right Model For Your Data 3 (Classification).srt |
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24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 |
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24. Evaluating A Machine Learning Model 2 (Cross Validation).srt |
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28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 |
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28. Evaluating A Classification Model 4 (Confusion Matrix).srt |
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29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 |
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29. Evaluating A Classification Model 5 (Confusion Matrix).srt |
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30. Evaluating A Classification Model 6 (Classification Report).mp4 |
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30. Evaluating A Classification Model 6 (Classification Report).srt |
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35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 |
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35. Evaluating A Model With Cross Validation and Scoring Parameter.srt |
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45.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html |
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/10. Supervised Learning Classification + Regression/ |
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/11. Milestone Project 1 Supervised Learning (Classification)/ |
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2.1 End-to-end Heart Disease Classification Notebook (same as in videos).html |
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2.3 End-to-end Heart Disease Classification Notebook (with annotations).html |
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21.1 End-to-end Heart Disease Classification Notebook (with annotations).html |
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/12. Milestone Project 2 Supervised Learning (Time Series Data)/ |
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2.2 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html |
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2.4 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html |
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19.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html |
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/13. Data Engineering/ |
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/14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/ |
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4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html |
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4.2 Google Colab (our workspace for the upcoming project).html |
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4.4 Google Colab IO example (how to get data in and out of your Colab notebook).html |
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4.5 End-to-end Dog Vision Notebook (the project we_ll be working through).html |
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5.1 Google Colab FAQ (things you should know about Google Colab).html |
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5.2 Google Colab (our workspace for the upcoming project).html |
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6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html |
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10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn_t the default).html |
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14.1 Documentation on how many images Google recommends for image problems.html |
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17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html |
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18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html |
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21.1 Yann LeCun_s (OG of deep learning) Tweet on Batch Sizes.html |
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23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html |
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24. Optional How machines learn and what_s going on behind the scenes.html |
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25.4 TensorFlow Hub (resource for pre-trained deep learning models and more).html |
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25.5 MobileNetV2 (the model we_re using) on TensorFlow Hub.html |
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27.1 The Softmax Function (activation function we use in our model).html |
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27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html |
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27.3 MobileNetV2 (the model we_re using) architecture explanation by Sik-Ho Tsang.html |
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28.1 [Article] How to choose loss _ activation functions when building a deep learning model.html |
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35.1 TensorFlow documentation for the unbatch() function.html |
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42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html |
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/15. UPLOADED BY FEB 14th Storytelling + Communication How To Present Your Projects/ |
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/16. Career Advice + Extra Bits/ |
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/17. Learn Python/ |
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0.1 KB |
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53.6 MB |
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8.1 KB |
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23.0 MB |
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5.7 KB |
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52.3 MB |
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8.7 KB |
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0.1 KB |
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20.1 MB |
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4.2 KB |
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0.1 KB |
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64.8 MB |
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11.0 KB |
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0.1 KB |
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28.7 MB |
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4.6 KB |
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0.1 KB |
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0.1 KB |
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29.0 MB |
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5.1 KB |
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42.4 MB |
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6.0 KB |
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0.1 KB |
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14.5 MB |
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3.0 KB |
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8.3 MB |
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2.2 KB |
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34.3 MB |
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7.3 KB |
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27.9 MB |
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3.7 KB |
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21.4 MB |
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4.3 KB |
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28.5 MB |
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5.4 KB |
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0.1 KB |
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44.4 MB |
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7.3 KB |
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0.1 KB |
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26.9 MB |
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5.8 KB |
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17.8 MB |
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3.1 KB |
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0.1 KB |
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38.8 MB |
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8.6 KB |
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67.4 MB |
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9.5 KB |
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0.1 KB |
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0.0 KB |
/18. Learn Python Part 2/ |
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21.3 MB |
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3.1 KB |
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78.2 MB |
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16.0 KB |
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29.4 MB |
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5.4 KB |
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44.9 MB |
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6.1 KB |
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0.2 KB |
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20.7 MB |
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4.9 KB |
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20.3 MB |
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4.6 KB |
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29.7 MB |
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8.3 KB |
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48.9 MB |
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8.6 KB |
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35.2 MB |
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8.3 KB |
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36.0 MB |
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7.7 KB |
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45.3 MB |
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7.0 KB |
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17.2 MB |
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3.7 KB |
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0.1 KB |
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29.7 MB |
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6.0 KB |
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26.0 MB |
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4.7 KB |
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29.7 MB |
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7.5 KB |
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27.2 MB |
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6.6 KB |
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23.3 MB |
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5.4 KB |
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52.0 MB |
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10.6 KB |
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0.1 KB |
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0.1 KB |
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52.7 MB |
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8.0 KB |
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21.2 MB |
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4.5 KB |
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0.1 KB |
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51.0 MB |
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9.4 KB |
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24.3 MB |
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5.0 KB |
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40.0 MB |
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6.1 KB |
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66.1 MB |
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15.3 KB |
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0.4 KB |
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32.2 MB |
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5.4 KB |
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18.2 MB |
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4.4 KB |
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20.6 MB |
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5.5 KB |
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45.1 MB |
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8.3 KB |
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22.9 MB |
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4.8 KB |
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0.1 KB |
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21.1 MB |
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3.9 KB |
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39.5 MB |
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8.7 KB |
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38.3 MB |
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6.8 KB |
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19.1 MB |
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4.2 KB |
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0.1 KB |
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20.1 MB |
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4.9 KB |
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70.6 MB |
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10.3 KB |
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40.2 MB |
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6.4 KB |
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24.7 MB |
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5.2 KB |
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22.3 MB |
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3.3 KB |
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54.8 MB |
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8.6 KB |
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55.9 MB |
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9.6 KB |
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37.1 MB |
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6.7 KB |
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23.0 MB |
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5.1 KB |
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0.1 KB |
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0.1 KB |
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1.1 KB |
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86.2 MB |
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13.0 KB |
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0.4 KB |
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55.6 MB |
|
10.8 KB |
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75.9 MB |
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12.8 KB |
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50.3 MB |
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7.7 KB |
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1.0 KB |
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0.0 KB |
/19. Bonus Learn Advanced Statistics and Mathematics for FREE!/ |
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0.7 KB |
/20. Where To Go From Here/ |
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0.9 KB |
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11.7 MB |
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3.7 KB |
/21. Extras/ |
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1.6 KB |
Total files 815 |
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