Sources utilized throughout this project are:
- Regularization Paths for Generalized Linear Models via Coordinate Descent Paper
- Fast Regularization Paths via Coordinate Descent Talk
- UC Berkeley Introduction to Machine Learning (EECS 189) Note on Linear Regression
- UC Berkeley Introduction to Machine Learning (EECS 189) Note on Optimization
- UC Berkeley Engineering Statistics, Quality Control, and Forecasting (IEOR 165) Note on Linear Regression
- UC Berkeley Engineering Statistics, Quality Control, and Forecasting (IEOR 165) Note on Bias-Variance Tradeoff
- UC Berkeley Engineering Statistics, Quality Control, and Forecasting (IEOR 165) Note on Regularization
- Stanford Statistics 305 Lecture on Ridge Regression and the Lasso
- The Elements of Statistical Learning Book
- Coordinate Descent Lecture from Carnegie Mellon University