STATISTICAL LEARNING AND DATA MINING
- Statistical Learning
- Linear Regression
- Resampling Methods
- Linear Model Selection and Regularization
- Moving Beyond Linearity
- Tree-Based Methods
- Support Vector Machines
- Unsupervised Learning
Statistical learning refers to a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine l earning. This course encompasses many methods such as the lasso and sparse regression, classification and regression trees, and boosting and support vector machines.
- Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, An Introduction to Statistical Learning with Applications in R
- Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition.