Expression Analysis, Clustering, and Classification in Machine Learning - Lecture 2

Expression Analysis, Clustering, and Classification in Machine Learning - Lecture 2

Manolis Kellis via YouTube Direct link

Summary

13 of 13

13 of 13

Summary

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Expression Analysis, Clustering, and Classification in Machine Learning - Lecture 2

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  1. 1 Intro
  2. 2 What is Machine Learning
  3. 3 Making Inferences about the World
  4. 4 Reversing the Arrows: Bayesian Inference
  5. 5 Clustering and Classification
  6. 6 AI vs. ML vs. Representation Learning vs. Generative AI
  7. 7 ML for Gene Expression Analysis
  8. 8 K-means Clustering
  9. 9 Gaussian Mixture Model Sampling
  10. 10 Hierarchical Clustering
  11. 11 Clustering of Documents and Free-Form Text
  12. 12 Naive Bayes Classification
  13. 13 Summary

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