(WORK IN PROGRESS)
Labs and Solutions to Applied Exercices to "An Introduction to Statistical Learning" in Python (instead of R).
- Chapter 2 Lab - Introduction to Python and Numpy
- Chapter 3 Lab - Linear Regression
- Chapter 4 Lab - Logistic Regression, LDA, QDA, and KNN
- Chapter 5 Lab - Cross-Validation and the Bootstrap
- Chapter 6 Lab 1 - Subset Selection Methods
- Chapter 6 Lab 2 - Ridge Regression and the Lasso
- Chapter 7 Lab - Non-Linear Modeling
- Chapter 8 Lab - Decision Trees
- Chapter 9 Lab - Support Vector Machines
- Chapter 10 Lab 1- Principal Component Analysis
- Chapter 10 Lab 2 - Clustering