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