Statistical-Machine-Learning (ISLR)

1. Linear models- Least Square Linear regression, Lasso, Ridge regression
2. Logistic regresion
3. Linear model selection and Regularization- Subset selection, Shrinkage methods
4. Non-Linear models- KNN, Polynomial regression,Splines, Basis functions
5. Tree based methods- Decision Tree, Random Forest, Bagging, Boosting
6. Unsupervised- PCA, SVM, K-means clustering, Hierarchial clustering