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[FreeTutorials.Us] cluster-analysis-unsupervised-machine-learning-python

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视频 2019-12-1 13:03 2024-12-27 17:36 219 310.82 MB 28
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文件列表
  1. 01 Introduction to Unsupervised Learning/001 Introduction and Outline.mp44.11MB
  2. 01 Introduction to Unsupervised Learning/002 What is unsupervised learning used for.mp47.58MB
  3. 01 Introduction to Unsupervised Learning/003 Why Use Clustering.mp46.64MB
  4. 01 Introduction to Unsupervised Learning/004 How to Succeed in this Course.mp48.78MB
  5. 02 K-Means Clustering/005 Visual Walkthrough of the K-Means Clustering Algorithm.mp44.87MB
  6. 02 K-Means Clustering/006 Soft K-Means.mp44.15MB
  7. 02 K-Means Clustering/007 The K-Means Objective Function.mp43.02MB
  8. 02 K-Means Clustering/008 Soft K-Means in Python Code.mp430.21MB
  9. 02 K-Means Clustering/009 Visualizing Each Step of K-Means.mp45.25MB
  10. 02 K-Means Clustering/010 Examples of where K-Means can fail.mp417MB
  11. 02 K-Means Clustering/011 Disadvantages of K-Means Clustering.mp43.87MB
  12. 02 K-Means Clustering/012 How to Evaluate a Clustering Purity Davies-Bouldin Index.mp411.39MB
  13. 02 K-Means Clustering/013 Using K-Means on Real Data MNIST.mp410.7MB
  14. 02 K-Means Clustering/014 One Way to Choose K.mp49.07MB
  15. 02 K-Means Clustering/015 K-Means Application Finding Clusters of Related Words.mp425.98MB
  16. 03 Hierarchical Clustering/016 Visual Walkthrough of Agglomerative Hierarchical Clustering.mp44.4MB
  17. 03 Hierarchical Clustering/017 Agglomerative Clustering Options.mp46.22MB
  18. 03 Hierarchical Clustering/018 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp411.85MB
  19. 04 Gaussian Mixture Models GMMs/019 Description of the Gaussian Mixture Model and How to Train a GMM.mp45.23MB
  20. 04 Gaussian Mixture Models GMMs/020 Comparison between GMM and K-Means.mp42.99MB
  21. 04 Gaussian Mixture Models GMMs/021 Write a Gaussian Mixture Model in Python Code.mp430.12MB
  22. 04 Gaussian Mixture Models GMMs/022 Practical Issues with GMM Singular Covariance.mp44.96MB
  23. 04 Gaussian Mixture Models GMMs/023 Kernel Density Estimation.mp43.7MB
  24. 04 Gaussian Mixture Models GMMs/024 Expectation-Maximization.mp43.5MB
  25. 04 Gaussian Mixture Models GMMs/025 Future Unsupervised Learning Algorithms You Will Learn.mp41.95MB
  26. 05 Appendix/026 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
  27. 05 Appendix/027 How to Code by Yourself part 1.mp424.53MB
  28. 05 Appendix/028 How to Code by Yourself part 2.mp414.8MB
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