Classical Machine Learning

Chapters

1. Learning FoundationsScaffold
2. Linear RegressionScaffold
3. Logistic RegressionScaffold
4. Trees and EnsemblesScaffold
5. Kernel Methods and Support-Vector MachinesScaffold
6. ClusteringScaffold
7. Principal Component AnalysisScaffold
8. Generalization and Model SelectionScaffold
9. Probabilistic Machine LearningScaffold

Books

• Understanding Machine Learning: From Theory to AlgorithmsShai Shalev-Shwartz, Shai Ben-David
• Probabilistic Machine Learning: An IntroductionKevin Murphy
• The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani, Jerome Friedman

Portfolio

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Writing

No published writing for this domain.