This covers problems from chapter 9 of ISLRv2, covering questions over Support Vector Machines.

Homework covering chapter 8 of ISLRv2, regarding Tree-Based Methods such as BART, decision tree, random forest, boosting, and bagging.

This covers problems from chapter 8 of ISLRv2 and others relating to tree based methods, including XGBoost, Random Forest, Decision Trees, Bagging, and Boosting.

Homework covering chapter 6 of ISLRv2, Linear Model Selection and Regularization. This specifically covers ridge regression, Lasso, PLS, PCR, and stepwise regression.

This covers problems from chapter 5 of ISLRv2, covering problems over resampling methods such as K Fold Cross Validation and the Bootstrap Method.

Problems over chapter 7 of ISLRv2, covering non linear modeling such as polynomial fits, step regression, and Generative Additive Models.

Practice problems covering classification from chapter 4 of Introduction to Statistical Learning in R v2.

This is covering chapter 12 of ISLRv2, over unsupervised learning. It is over topics such as Principal Components Analysis, K means clustering, and hierarchical clustering.

Assignment 2 of STA6543, covering chapter 3 of ISLR2 and the basics of linear regression.

Homework problems over chapter 2 of ISLRv2, covering basic questions of classification and regression.

Homework 4 covering Chapter 6 of ISLR on Linear Model Selection and Regularization.

Homework 3 for STA 6923, taken from Chapter 4 of ISLR.