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DesireCourse Net Udemy Cluster Analysis and Unsupervised Machine Learning in Python

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[DesireCourse.Net] Udemy - Cluster Analysis and Unsupervised Machine Learning in Python

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Total Size

924.3 MB

Total Files

80

Hash

D6DEF40031F087EF0911ECF51D1247DB300B31AA

/1. Introduction to Unsupervised Learning/

1. Introduction and Outline.mp4

4.3 MB

1. Introduction and Outline.vtt

3.3 KB

2. What is unsupervised learning used for.mp4

7.9 MB

2. What is unsupervised learning used for.vtt

5.4 KB

3. Why Use Clustering.mp4

7.0 MB

3. Why Use Clustering.vtt

5.3 KB

4. How to Succeed in this Course.mp4

3.5 MB

4. How to Succeed in this Course.vtt

3.6 KB

/2. K-Means Clustering/

1. An Easy Introduction to K-Means Clustering.mp4

13.2 MB

1. An Easy Introduction to K-Means Clustering.vtt

8.5 KB

10. Using K-Means on Real Data MNIST.mp4

11.2 MB

10. Using K-Means on Real Data MNIST.vtt

6.4 KB

11. One Way to Choose K.mp4

9.5 MB

11. One Way to Choose K.vtt

4.6 KB

12. K-Means Application Finding Clusters of Related Words.mp4

27.2 MB

12. K-Means Application Finding Clusters of Related Words.vtt

7.5 KB

2. Visual Walkthrough of the K-Means Clustering Algorithm.mp4

5.1 MB

2. Visual Walkthrough of the K-Means Clustering Algorithm.vtt

3.4 KB

3. Soft K-Means.mp4

26.5 MB

3. Soft K-Means.vtt

6.3 KB

4. The K-Means Objective Function.mp4

3.2 MB

4. The K-Means Objective Function.vtt

1.9 KB

5. Soft K-Means in Python Code.mp4

31.7 MB

5. Soft K-Means in Python Code.vtt

7.1 KB

6. Visualizing Each Step of K-Means.mp4

5.5 MB

6. Visualizing Each Step of K-Means.vtt

2.5 KB

7. Examples of where K-Means can fail.mp4

17.8 MB

7. Examples of where K-Means can fail.vtt

4.6 KB

8. Disadvantages of K-Means Clustering.mp4

4.1 MB

8. Disadvantages of K-Means Clustering.vtt

3.0 KB

9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4

11.9 MB

9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).vtt

8.3 KB

/3. Hierarchical Clustering/

1. Visual Walkthrough of Agglomerative Hierarchical Clustering.mp4

4.6 MB

1. Visual Walkthrough of Agglomerative Hierarchical Clustering.vtt

3.2 KB

2. Agglomerative Clustering Options.mp4

6.5 MB

2. Agglomerative Clustering Options.vtt

5.0 KB

3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4

12.4 MB

3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.vtt

4.0 KB

4. Application Evolution.mp4

27.7 MB

4. Application Evolution.vtt

14.7 KB

5. Application Donald Trump vs. Hillary Clinton Tweets.mp4

37.0 MB

5. Application Donald Trump vs. Hillary Clinton Tweets.vtt

17.3 KB

/4. Gaussian Mixture Models (GMMs)/

1. Description of the Gaussian Mixture Model and How to Train a GMM.mp4

5.5 MB

1. Description of the Gaussian Mixture Model and How to Train a GMM.vtt

3.4 KB

2. Comparison between GMM and K-Means.mp4

3.2 MB

2. Comparison between GMM and K-Means.vtt

2.1 KB

3. Write a Gaussian Mixture Model in Python Code.mp4

31.6 MB

3. Write a Gaussian Mixture Model in Python Code.vtt

7.0 KB

4. Practical Issues with GMM Singular Covariance.mp4

5.2 MB

4. Practical Issues with GMM Singular Covariance.vtt

3.7 KB

5. Kernel Density Estimation.mp4

3.9 MB

5. Kernel Density Estimation.vtt

3.0 KB

6. Expectation-Maximization.mp4

3.7 MB

6. Expectation-Maximization.vtt

2.5 KB

7. Future Unsupervised Learning Algorithms You Will Learn.mp4

2.0 MB

7. Future Unsupervised Learning Algorithms You Will Learn.vtt

1.3 KB

/5. Appendix/

1. What is the Appendix.mp4

5.7 MB

1. What is the Appendix.vtt

3.4 KB

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

30.8 MB

10. What order should I take your courses in (part 1).vtt

14.4 KB

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

39.5 MB

11. What order should I take your courses in (part 2).vtt

20.7 KB

2. Windows-Focused Environment Setup 2018.mp4

195.4 MB

2. Windows-Focused Environment Setup 2018.vtt

17.8 KB

3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4

46.1 MB

3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt

12.7 KB

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

25.7 MB

4. How to Code by Yourself (part 1).vtt

20.3 KB

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

15.5 MB

5. How to Code by Yourself (part 2).vtt

11.9 KB

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

19.2 MB

6. How to Succeed in this Course (Long Version).vtt

13.1 KB

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

40.8 MB

7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt

28.4 KB

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

82.1 MB

8. Proof that using Jupyter Notebook is the same as not using it.vtt

82.1 MB

9. Python 2 vs Python 3.mp4

8.2 MB

9. Python 2 vs Python 3.vtt

5.5 KB

/

[CourseClub.Me].url

0.0 KB

[DesireCourse.Net].url

0.1 KB

 

Total files 80


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