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Download [Tutorialsplanet.NET] Udemy - Data Science Supervised Machine Learning in Python

Tutorialsplanet NET Udemy Data Science Supervised Machine Learning in Python

Name

[Tutorialsplanet.NET] Udemy - Data Science Supervised Machine Learning in Python

 DOWNLOAD Copy Link

Total Size

1.3 GB

Total Files

105

Hash

20E70EA2FE4E2F2ADCD081CB21877D2F67612401

/1. Introduction and Review/

1. Introduction and Outline.mp4

8.0 MB

1. Introduction and Outline.srt

5.8 KB

2. Review of Important Concepts.mp4

6.3 MB

2. Review of Important Concepts.srt

4.5 KB

3. Where to get the Code and Data.mp4

4.0 MB

3. Where to get the Code and Data.srt

2.7 KB

4. How to Succeed in this Course.mp4

3.5 MB

4. How to Succeed in this Course.srt

4.1 KB

/2. K-Nearest Neighbor/

1. K-Nearest Neighbor Intuition.mp4

18.4 MB

1. K-Nearest Neighbor Intuition.srt

5.0 KB

2. K-Nearest Neighbor Concepts.mp4

9.0 MB

2. K-Nearest Neighbor Concepts.srt

6.4 KB

3. KNN in Code with MNIST.mp4

18.8 MB

3. KNN in Code with MNIST.srt

34.0 MB

4. When KNN Can Fail.mp4

8.1 MB

4. When KNN Can Fail.srt

4.7 KB

5. KNN for the XOR Problem.mp4

4.5 MB

5. KNN for the XOR Problem.srt

2.2 KB

6. KNN for the Donut Problem.mp4

5.7 MB

6. KNN for the Donut Problem.srt

74.6 MB

7. Effect of K.mp4

37.5 MB

7. Effect of K.srt

44.6 MB

8. KNN Exercise.mp4

17.7 MB

8. KNN Exercise.srt

5.6 KB

/3. Naive Bayes and Bayes Classifiers/

1. Bayes Classifier Intuition (Continuous).mp4

84.1 MB

1. Bayes Classifier Intuition (Continuous).srt

23.5 KB

2. Bayes Classifier Intuition (Discrete).mp4

52.5 MB

2. Bayes Classifier Intuition (Discrete).srt

13.2 KB

3. Naive Bayes.mp4

16.5 MB

3. Naive Bayes.srt

11.8 KB

4. Naive Bayes Handwritten Example.mp4

6.1 MB

4. Naive Bayes Handwritten Example.srt

3.7 KB

5. Naive Bayes in Code with MNIST.mp4

15.1 MB

5. Naive Bayes in Code with MNIST.srt

4.9 KB

6. Non-Naive Bayes.mp4

7.7 MB

6. Non-Naive Bayes.srt

5.0 KB

7. Bayes Classifier in Code with MNIST.mp4

4.7 MB

7. Bayes Classifier in Code with MNIST.srt

6.5 MB

8. Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).mp4

10.9 MB

8. Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).srt

7.6 KB

9. Generative vs Discriminative Models.mp4

5.4 MB

9. Generative vs Discriminative Models.srt

3.2 KB

/4. Decision Trees/

1. Decision Tree Intuition.mp4

21.4 MB

1. Decision Tree Intuition.srt

5.7 KB

2. Decision Tree Basics.mp4

8.7 MB

2. Decision Tree Basics.srt

6.3 KB

3. Information Entropy.mp4

7.3 MB

3. Information Entropy.srt

4.4 KB

4. Maximizing Information Gain.mp4

14.6 MB

4. Maximizing Information Gain.srt

9.9 KB

5. Choosing the Best Split.mp4

7.0 MB

5. Choosing the Best Split.srt

4.9 KB

6. Decision Tree in Code.mp4

31.8 MB

6. Decision Tree in Code.srt

11.4 KB

/5. Perceptrons/

1. Perceptron Concepts.mp4

12.8 MB

1. Perceptron Concepts.srt

8.9 KB

2. Perceptron in Code.mp4

14.4 MB

2. Perceptron in Code.srt

4.8 KB

3. Perceptron for MNIST and XOR.mp4

9.2 MB

3. Perceptron for MNIST and XOR.srt

2.4 KB

4. Perceptron Loss Function.mp4

6.6 MB

4. Perceptron Loss Function.srt

5.0 KB

/6. Practical Machine Learning/

1. Hyperparameters and Cross-Validation.mp4

7.8 MB

1. Hyperparameters and Cross-Validation.srt

5.2 KB

2. Feature Extraction and Feature Selection.mp4

7.4 MB

2. Feature Extraction and Feature Selection.srt

5.0 KB

3. Comparison to Deep Learning.mp4

9.1 MB

3. Comparison to Deep Learning.srt

6.2 KB

4. Multiclass Classification.mp4

5.9 MB

4. Multiclass Classification.srt

4.2 KB

5. Sci-Kit Learn.mp4

16.6 MB

5. Sci-Kit Learn.srt

11.4 KB

6. Regression with Sci-Kit Learn is Easy.mp4

11.3 MB

6. Regression with Sci-Kit Learn is Easy.srt

6.2 KB

/7. Building a Machine Learning Web Service/

1. Building a Machine Learning Web Service Concepts.mp4

7.6 MB

1. Building a Machine Learning Web Service Concepts.srt

5.5 KB

2. Building a Machine Learning Web Service Code.mp4

12.4 MB

2. Building a Machine Learning Web Service Code.srt

7.6 KB

/8. Conclusion/

1. What’s Next Support Vector Machines and Ensemble Methods (e.g. Random Forest).mp4

6.6 MB

1. What’s Next Support Vector Machines and Ensemble Methods (e.g. Random Forest).srt

3.6 KB

/9. Appendix FAQ/

1. What is the Appendix.mp4

5.7 MB

1. What is the Appendix.srt

3.8 KB

10. Python 2 vs Python 3.mp4

8.2 MB

10. Python 2 vs Python 3.srt

6.2 KB

11. What order should I take your courses in (part 1).mp4

30.7 MB

11. What order should I take your courses in (part 1).srt

16.4 KB

12. What order should I take your courses in (part 2).mp4

39.5 MB

12. What order should I take your courses in (part 2).srt

39.5 MB

2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4

39.7 MB

2. BONUS Where to get Udemy coupons and FREE deep learning material.srt

8.1 KB

3. Windows-Focused Environment Setup 2018.mp4

195.4 MB

3. Windows-Focused Environment Setup 2018.srt

20.6 KB

4. How to install Numpy, Scipy, Matplotlib, and Sci-Kit Learn.mp4

46.1 MB

4. How to install Numpy, Scipy, Matplotlib, and Sci-Kit Learn.srt

14.8 KB

5. How to Code by Yourself (part 1).mp4

25.7 MB

5. How to Code by Yourself (part 1).srt

23.3 KB

6. How to Code by Yourself (part 2).mp4

15.5 MB

6. How to Code by Yourself (part 2).srt

13.6 KB

7. How to Succeed in this Course (Long Version).mp4

13.6 MB

7. How to Succeed in this Course (Long Version).srt

15.0 KB

8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4

40.9 MB

8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt

32.5 KB

9. Proof that using Jupyter Notebook is the same as not using it.mp4

82.1 MB

9. Proof that using Jupyter Notebook is the same as not using it.srt

14.5 KB

/

[Tutorialsplanet.NET].url

0.1 KB

 

Total files 105


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