Udemy - Cluster Analysis and Unsupervised Machine Learning in Python (11.2023)

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Udemy - Cluster Analysis and Unsupervised Machine Learning in Python (11.2023)

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种子哈希：35f990946ad5ac27143c674cf93e9ee387f7699d
文件大小： 1.61G
已经下载：91次
下载速度：极快
收录时间：2025-07-31
最近下载：2025-10-11

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文件列表

  • 05 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.mp4 176.1 MB
  • 04 - Gaussian Mixture Models (GMMs)/002 Write a Gaussian Mixture Model in Python Code.mp4 112.4 MB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 85.2 MB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.4 MB
  • 05 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 78.3 MB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.mp4 67.4 MB
  • 02 - K-Means Clustering/020 K-Means Application Finding Clusters of Related Words.mp4 67.1 MB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).mp4 58.8 MB
  • 01 - Introduction to Unsupervised Learning/004 Why Use Clustering.mp4 57.5 MB
  • 02 - K-Means Clustering/007 Hard K-Means Exercise 3 Solution.mp4 56.3 MB
  • 01 - Introduction to Unsupervised Learning/001 Introduction.mp4 47.9 MB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 44.5 MB
  • 03 - Hierarchical Clustering/004 Application Evolution.mp4 43.2 MB
  • 03 - Hierarchical Clustering/005 Application Donald Trump vs. Hillary Clinton Tweets.mp4 42.7 MB
  • 08 - Appendix FAQ Finale/002 BONUS.mp4 41.8 MB
  • 02 - K-Means Clustering/012 Soft K-Means in Python Code.mp4 37.2 MB
  • 02 - K-Means Clustering/003 Hard K-Means Exercise 1 Solution.mp4 32.0 MB
  • 01 - Introduction to Unsupervised Learning/003 What is unsupervised learning used for.mp4 30.5 MB
  • 04 - Gaussian Mixture Models (GMMs)/001 Gaussian Mixture Model (GMM) Algorithm.mp4 29.0 MB
  • 02 - K-Means Clustering/022 Suggestion Box.mp4 28.4 MB
  • 02 - K-Means Clustering/008 Hard K-Means Objective Theory.mp4 27.3 MB
  • 02 - K-Means Clustering/017 How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 27.1 MB
  • 02 - K-Means Clustering/015 Examples of where K-Means can fail.mp4 25.8 MB
  • 02 - K-Means Clustering/002 Hard K-Means Exercise Prompt 1.mp4 25.1 MB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).mp4 21.9 MB
  • 02 - K-Means Clustering/009 Hard K-Means Objective Code.mp4 21.8 MB
  • 04 - Gaussian Mixture Models (GMMs)/008 Expectation-Maximization (pt 1).mp4 21.8 MB
  • 04 - Gaussian Mixture Models (GMMs)/007 GMM vs Bayes Classifier (pt 2).mp4 19.7 MB
  • 04 - Gaussian Mixture Models (GMMs)/003 Practical Issues with GMM Singular Covariance.mp4 19.5 MB
  • 02 - K-Means Clustering/018 Using K-Means on Real Data MNIST.mp4 19.2 MB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 04 - Gaussian Mixture Models (GMMs)/006 GMM vs Bayes Classifier (pt 1).mp4 18.1 MB
  • 01 - Introduction to Unsupervised Learning/006 How to Succeed in this Course.mp4 17.0 MB
  • 02 - K-Means Clustering/001 An Easy Introduction to K-Means Clustering.mp4 17.0 MB
  • 02 - K-Means Clustering/006 Hard K-Means Exercise Prompt 3.mp4 16.4 MB
  • 02 - K-Means Clustering/021 Clustering for NLP and Computer Vision Real-World Applications.mp4 15.9 MB
  • 02 - K-Means Clustering/005 Hard K-Means Exercise 2 Solution.mp4 15.8 MB
  • 04 - Gaussian Mixture Models (GMMs)/010 Expectation-Maximization (pt 3).mp4 13.7 MB
  • 04 - Gaussian Mixture Models (GMMs)/005 Kernel Density Estimation.mp4 13.3 MB
  • 03 - Hierarchical Clustering/003 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 10.7 MB
  • 02 - K-Means Clustering/010 Soft K-Means.mp4 10.5 MB
  • 02 - K-Means Clustering/019 One Way to Choose K.mp4 10.1 MB
  • 01 - Introduction to Unsupervised Learning/005 Where to get the code.mp4 9.8 MB
  • 02 - K-Means Clustering/004 Hard K-Means Exercise Prompt 2.mp4 9.8 MB
  • 02 - K-Means Clustering/014 Visualizing Each Step of K-Means.mp4 9.5 MB
  • 05 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.mp4 9.4 MB
  • 01 - Introduction to Unsupervised Learning/002 Course Outline.mp4 9.1 MB
  • 04 - Gaussian Mixture Models (GMMs)/004 Comparison between GMM and K-Means.mp4 8.4 MB
  • 02 - K-Means Clustering/013 How to Pace Yourself.mp4 8.3 MB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.mp4 8.0 MB
  • 08 - Appendix FAQ Finale/001 What is the Appendix.mp4 6.4 MB
  • 03 - Hierarchical Clustering/002 Agglomerative Clustering Options.mp4 5.7 MB
  • 02 - K-Means Clustering/016 Disadvantages of K-Means Clustering.mp4 4.7 MB
  • 04 - Gaussian Mixture Models (GMMs)/009 Expectation-Maximization (pt 2).mp4 4.6 MB
  • 03 - Hierarchical Clustering/001 Visual Walkthrough of Agglomerative Hierarchical Clustering.mp4 4.0 MB
  • 02 - K-Means Clustering/011 The Soft K-Means Objective Function.mp4 3.3 MB
  • 04 - Gaussian Mixture Models (GMMs)/011 Future Unsupervised Learning Algorithms You Will Learn.mp4 2.3 MB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.5 kB
  • 04 - Gaussian Mixture Models (GMMs)/002 Write a Gaussian Mixture Model in Python Code.srt 25.5 kB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.6 kB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).srt 23.3 kB
  • 02 - K-Means Clustering/007 Hard K-Means Exercise 3 Solution.srt 21.0 kB
  • 04 - Gaussian Mixture Models (GMMs)/001 Gaussian Mixture Model (GMM) Algorithm.srt 20.6 kB
  • 05 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.srt 20.6 kB
  • 03 - Hierarchical Clustering/005 Application Donald Trump vs. Hillary Clinton Tweets.srt 19.9 kB
  • 02 - K-Means Clustering/008 Hard K-Means Objective Theory.srt 17.4 kB
  • 03 - Hierarchical Clustering/004 Application Evolution.srt 16.6 kB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.4 kB
  • 04 - Gaussian Mixture Models (GMMs)/008 Expectation-Maximization (pt 1).srt 15.3 kB
  • 04 - Gaussian Mixture Models (GMMs)/007 GMM vs Bayes Classifier (pt 2).srt 15.0 kB
  • 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).srt 14.9 kB
  • 05 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.8 kB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.srt 14.5 kB
  • 02 - K-Means Clustering/003 Hard K-Means Exercise 1 Solution.srt 14.2 kB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).srt 13.6 kB
  • 04 - Gaussian Mixture Models (GMMs)/006 GMM vs Bayes Classifier (pt 1).srt 12.8 kB
  • 01 - Introduction to Unsupervised Learning/004 Why Use Clustering.srt 12.4 kB
  • 04 - Gaussian Mixture Models (GMMs)/003 Practical Issues with GMM Singular Covariance.srt 12.4 kB
  • 02 - K-Means Clustering/002 Hard K-Means Exercise Prompt 1.srt 11.8 kB
  • 04 - Gaussian Mixture Models (GMMs)/010 Expectation-Maximization (pt 3).srt 10.3 kB
  • 02 - K-Means Clustering/001 An Easy Introduction to K-Means Clustering.srt 9.7 kB
  • 02 - K-Means Clustering/021 Clustering for NLP and Computer Vision Real-World Applications.srt 9.4 kB
  • 02 - K-Means Clustering/006 Hard K-Means Exercise Prompt 3.srt 8.9 kB
  • 02 - K-Means Clustering/017 How to Evaluate a Clustering (Purity, Davies-Bouldin Index).srt 8.9 kB
  • 02 - K-Means Clustering/005 Hard K-Means Exercise 2 Solution.srt 8.6 kB
  • 04 - Gaussian Mixture Models (GMMs)/005 Kernel Density Estimation.srt 8.6 kB
  • 02 - K-Means Clustering/020 K-Means Application Finding Clusters of Related Words.srt 8.6 kB
  • 08 - Appendix FAQ Finale/002 BONUS.srt 8.0 kB
  • 02 - K-Means Clustering/012 Soft K-Means in Python Code.srt 7.7 kB
  • 01 - Introduction to Unsupervised Learning/003 What is unsupervised learning used for.srt 7.4 kB
  • 02 - K-Means Clustering/010 Soft K-Means.srt 7.1 kB
  • 01 - Introduction to Unsupervised Learning/001 Introduction.srt 7.1 kB
  • 02 - K-Means Clustering/018 Using K-Means on Real Data MNIST.srt 6.9 kB
  • 05 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.srt 6.8 kB
  • 01 - Introduction to Unsupervised Learning/005 Where to get the code.srt 6.4 kB
  • 02 - K-Means Clustering/004 Hard K-Means Exercise Prompt 2.srt 6.3 kB
  • 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.srt 6.2 kB
  • 01 - Introduction to Unsupervised Learning/002 Course Outline.srt 6.1 kB
  • 02 - K-Means Clustering/009 Hard K-Means Objective Code.srt 6.1 kB
  • 03 - Hierarchical Clustering/002 Agglomerative Clustering Options.srt 5.4 kB
  • 02 - K-Means Clustering/015 Examples of where K-Means can fail.srt 5.3 kB
  • 02 - K-Means Clustering/019 One Way to Choose K.srt 5.2 kB
  • 04 - Gaussian Mixture Models (GMMs)/004 Comparison between GMM and K-Means.srt 5.1 kB
  • 02 - K-Means Clustering/022 Suggestion Box.srt 4.9 kB
  • 02 - K-Means Clustering/013 How to Pace Yourself.srt 4.8 kB
  • 01 - Introduction to Unsupervised Learning/006 How to Succeed in this Course.srt 4.5 kB
  • 03 - Hierarchical Clustering/003 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.srt 4.3 kB
  • 08 - Appendix FAQ Finale/001 What is the Appendix.srt 3.8 kB
  • 03 - Hierarchical Clustering/001 Visual Walkthrough of Agglomerative Hierarchical Clustering.srt 3.5 kB
  • 02 - K-Means Clustering/016 Disadvantages of K-Means Clustering.srt 3.2 kB
  • 04 - Gaussian Mixture Models (GMMs)/009 Expectation-Maximization (pt 2).srt 2.7 kB
  • 02 - K-Means Clustering/014 Visualizing Each Step of K-Means.srt 2.6 kB
  • 02 - K-Means Clustering/011 The Soft K-Means Objective Function.srt 2.0 kB
  • 04 - Gaussian Mixture Models (GMMs)/011 Future Unsupervised Learning Algorithms You Will Learn.srt 1.4 kB
  • 01 - Introduction to Unsupervised Learning/005 Github-Link.url 83 Bytes
  • 01 - Introduction to Unsupervised Learning/external-links.txt 80 Bytes

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