Udemy - Cluster Analysis and Unsupervised Machine Learning in Python (11.2023)
File List
- 05 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.mp4 168.0 MB
- 04 - Gaussian Mixture Models (GMMs)/002 Write a Gaussian Mixture Model in Python Code.mp4 107.2 MB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 81.2 MB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 75.8 MB
- 05 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 74.7 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 64.3 MB
- 02 - K-Means Clustering/020 K-Means Application Finding Clusters of Related Words.mp4 63.9 MB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).mp4 56.1 MB
- 01 - Introduction to Unsupervised Learning/004 Why Use Clustering.mp4 54.8 MB
- 02 - K-Means Clustering/007 Hard K-Means Exercise 3 Solution.mp4 53.7 MB
- 01 - Introduction to Unsupervised Learning/001 Introduction.mp4 45.6 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 42.5 MB
- 03 - Hierarchical Clustering/004 Application Evolution.mp4 41.2 MB
- 03 - Hierarchical Clustering/005 Application Donald Trump vs. Hillary Clinton Tweets.mp4 40.7 MB
- 08 - Appendix FAQ Finale/002 BONUS.mp4 39.9 MB
- 02 - K-Means Clustering/012 Soft K-Means in Python Code.mp4 35.4 MB
- 02 - K-Means Clustering/003 Hard K-Means Exercise 1 Solution.mp4 30.5 MB
- 01 - Introduction to Unsupervised Learning/003 What is unsupervised learning used for.mp4 29.1 MB
- 04 - Gaussian Mixture Models (GMMs)/001 Gaussian Mixture Model (GMM) Algorithm.mp4 27.6 MB
- 02 - K-Means Clustering/022 Suggestion Box.mp4 27.1 MB
- 02 - K-Means Clustering/008 Hard K-Means Objective Theory.mp4 26.1 MB
- 02 - K-Means Clustering/017 How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 25.8 MB
- 02 - K-Means Clustering/015 Examples of where K-Means can fail.mp4 24.6 MB
- 02 - K-Means Clustering/002 Hard K-Means Exercise Prompt 1.mp4 23.9 MB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).mp4 20.9 MB
- 02 - K-Means Clustering/009 Hard K-Means Objective Code.mp4 20.8 MB
- 04 - Gaussian Mixture Models (GMMs)/008 Expectation-Maximization (pt 1).mp4 20.8 MB
- 04 - Gaussian Mixture Models (GMMs)/007 GMM vs Bayes Classifier (pt 2).mp4 18.8 MB
- 04 - Gaussian Mixture Models (GMMs)/003 Practical Issues with GMM Singular Covariance.mp4 18.6 MB
- 02 - K-Means Clustering/018 Using K-Means on Real Data MNIST.mp4 18.3 MB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).mp4 17.9 MB
- 04 - Gaussian Mixture Models (GMMs)/006 GMM vs Bayes Classifier (pt 1).mp4 17.3 MB
- 01 - Introduction to Unsupervised Learning/006 How to Succeed in this Course.mp4 16.2 MB
- 02 - K-Means Clustering/001 An Easy Introduction to K-Means Clustering.mp4 16.2 MB
- 02 - K-Means Clustering/006 Hard K-Means Exercise Prompt 3.mp4 15.6 MB
- 02 - K-Means Clustering/021 Clustering for NLP and Computer Vision Real-World Applications.mp4 15.2 MB
- 02 - K-Means Clustering/005 Hard K-Means Exercise 2 Solution.mp4 15.1 MB
- 04 - Gaussian Mixture Models (GMMs)/010 Expectation-Maximization (pt 3).mp4 13.1 MB
- 04 - Gaussian Mixture Models (GMMs)/005 Kernel Density Estimation.mp4 12.7 MB
- 03 - Hierarchical Clustering/003 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 10.2 MB
- 02 - K-Means Clustering/010 Soft K-Means.mp4 10.0 MB
- 02 - K-Means Clustering/019 One Way to Choose K.mp4 9.6 MB
- 01 - Introduction to Unsupervised Learning/005 Where to get the code.mp4 9.4 MB
- 02 - K-Means Clustering/004 Hard K-Means Exercise Prompt 2.mp4 9.3 MB
- 02 - K-Means Clustering/014 Visualizing Each Step of K-Means.mp4 9.0 MB
- 05 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.mp4 8.9 MB
- 01 - Introduction to Unsupervised Learning/002 Course Outline.mp4 8.7 MB
- 04 - Gaussian Mixture Models (GMMs)/004 Comparison between GMM and K-Means.mp4 8.0 MB
- 02 - K-Means Clustering/013 How to Pace Yourself.mp4 7.9 MB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.mp4 7.6 MB
- 08 - Appendix FAQ Finale/001 What is the Appendix.mp4 6.1 MB
- 03 - Hierarchical Clustering/002 Agglomerative Clustering Options.mp4 5.5 MB
- 02 - K-Means Clustering/016 Disadvantages of K-Means Clustering.mp4 4.5 MB
- 04 - Gaussian Mixture Models (GMMs)/009 Expectation-Maximization (pt 2).mp4 4.4 MB
- 03 - Hierarchical Clustering/001 Visual Walkthrough of Agglomerative Hierarchical Clustering.mp4 3.9 MB
- 02 - K-Means Clustering/011 The Soft K-Means Objective Function.mp4 3.2 MB
- 04 - Gaussian Mixture Models (GMMs)/011 Future Unsupervised Learning Algorithms You Will Learn.mp4 2.2 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 31.8 KB
- 04 - Gaussian Mixture Models (GMMs)/002 Write a Gaussian Mixture Model in Python Code.srt 24.9 KB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.0 KB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).srt 22.8 KB
- 02 - K-Means Clustering/007 Hard K-Means Exercise 3 Solution.srt 20.5 KB
- 04 - Gaussian Mixture Models (GMMs)/001 Gaussian Mixture Model (GMM) Algorithm.srt 20.2 KB
- 05 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.srt 20.1 KB
- 03 - Hierarchical Clustering/005 Application Donald Trump vs. Hillary Clinton Tweets.srt 19.4 KB
- 02 - K-Means Clustering/008 Hard K-Means Objective Theory.srt 16.9 KB
- 03 - Hierarchical Clustering/004 Application Evolution.srt 16.2 KB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.0 KB
- 04 - Gaussian Mixture Models (GMMs)/008 Expectation-Maximization (pt 1).srt 14.9 KB
- 04 - Gaussian Mixture Models (GMMs)/007 GMM vs Bayes Classifier (pt 2).srt 14.6 KB
- 07 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).srt 14.5 KB
- 05 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.5 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 14.1 KB
- 02 - K-Means Clustering/003 Hard K-Means Exercise 1 Solution.srt 13.8 KB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).srt 13.3 KB
- 04 - Gaussian Mixture Models (GMMs)/006 GMM vs Bayes Classifier (pt 1).srt 12.5 KB
- 01 - Introduction to Unsupervised Learning/004 Why Use Clustering.srt 12.1 KB
- 04 - Gaussian Mixture Models (GMMs)/003 Practical Issues with GMM Singular Covariance.srt 12.1 KB
- 02 - K-Means Clustering/002 Hard K-Means Exercise Prompt 1.srt 11.5 KB
- 04 - Gaussian Mixture Models (GMMs)/010 Expectation-Maximization (pt 3).srt 10.1 KB
- 02 - K-Means Clustering/001 An Easy Introduction to K-Means Clustering.srt 9.4 KB
- 02 - K-Means Clustering/021 Clustering for NLP and Computer Vision Real-World Applications.srt 9.1 KB
- 02 - K-Means Clustering/006 Hard K-Means Exercise Prompt 3.srt 8.7 KB
- 02 - K-Means Clustering/017 How to Evaluate a Clustering (Purity, Davies-Bouldin Index).srt 8.7 KB
- 02 - K-Means Clustering/005 Hard K-Means Exercise 2 Solution.srt 8.4 KB
- 04 - Gaussian Mixture Models (GMMs)/005 Kernel Density Estimation.srt 8.4 KB
- 02 - K-Means Clustering/020 K-Means Application Finding Clusters of Related Words.srt 8.4 KB
- 08 - Appendix FAQ Finale/002 BONUS.srt 7.8 KB
- 02 - K-Means Clustering/012 Soft K-Means in Python Code.srt 7.5 KB
- 01 - Introduction to Unsupervised Learning/003 What is unsupervised learning used for.srt 7.2 KB
- 02 - K-Means Clustering/010 Soft K-Means.srt 7.0 KB
- 01 - Introduction to Unsupervised Learning/001 Introduction.srt 6.9 KB
- 02 - K-Means Clustering/018 Using K-Means on Real Data MNIST.srt 6.7 KB
- 05 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.srt 6.6 KB
- 01 - Introduction to Unsupervised Learning/005 Where to get the code.srt 6.3 KB
- 02 - K-Means Clustering/004 Hard K-Means Exercise Prompt 2.srt 6.1 KB
- 06 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.srt 6.1 KB
- 01 - Introduction to Unsupervised Learning/002 Course Outline.srt 6.0 KB
- 02 - K-Means Clustering/009 Hard K-Means Objective Code.srt 6.0 KB
- 03 - Hierarchical Clustering/002 Agglomerative Clustering Options.srt 5.2 KB
- 02 - K-Means Clustering/015 Examples of where K-Means can fail.srt 5.2 KB
- 02 - K-Means Clustering/019 One Way to Choose K.srt 5.1 KB
- 04 - Gaussian Mixture Models (GMMs)/004 Comparison between GMM and K-Means.srt 5.0 KB
- 02 - K-Means Clustering/022 Suggestion Box.srt 4.7 KB
- 02 - K-Means Clustering/013 How to Pace Yourself.srt 4.7 KB
- 01 - Introduction to Unsupervised Learning/006 How to Succeed in this Course.srt 4.4 KB
- 03 - Hierarchical Clustering/003 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.srt 4.2 KB
- 08 - Appendix FAQ Finale/001 What is the Appendix.srt 3.7 KB
- 03 - Hierarchical Clustering/001 Visual Walkthrough of Agglomerative Hierarchical Clustering.srt 3.4 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 2.6 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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