Reading Notes on Elements of Statistical Learning, Summer 2014

     

    Chap 1. Introduction

    Chap 2. Supervised Learning

    Chap 3. Regression

    Chap 4. Classification

    Chap 5. Basis

    Chap 6. Kernel

    Chap 7. Assessment

    Chap 8. Inference [Slides] [mcodes]

    Chap 9. Trees

    Chap 10. Boosting

    Chap 11. Neural Networks

    Chap 12. SVM

    Chap 13. Nearest Neighbors

    Chap 14. Unsupervised Learning

    Chap 15. Random Forests

    Chap 16. Ensemble Learning

    Chap 17. Undirected Graphical Models [Slides] [mcodes]

    Chap 18. High Dimemsional Problems

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