Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

Sparse regression is an important topic in data science and machine learning that allows one to build models with as few variables as possible, making these models interpretable and robust to overfitting. Here we discuss sparse regression and the LASSO algorithm.   Original paper by Tibshirani (1996): http://statweb.stanford.edu/~tibs/lasso/lasso.pdf Book Website: http://databookuw.com Book PDF: http://databookuw.com/databook.pdf These lectures follow Chapter 3 from: "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz Amazon: https://www.amazon.com/Data-Driven-Science-Engineering-Learning-Dynamical/dp/1108422098/ Brunton Website: eigensteve.com This video was produced at the University of Washington