**STAT740 Foundation of Statistical Machine Leanring - Fall 2020**

- Syllabus
- Office Hour: TR 11:00am-12:00pm or by appointment; a zoom link will be send for office hour.
- Lecture notes
- Class lecture notes
- See Canvas.

- HWs
- See Canvas.

- Class lecture notes
- Recommeded Textbooks
- The Elements of Statistical Learning. Hastie, Tibshirani, and Friedman. Springer, 2009 (2nd Edition). 1st Edition is in 2001.
- Statistics for High-Dimensional Data: Methods, Theory and Applications. Buuhlmann and Van de Geer. Springer, 2011.
- Foundations of Machine Learning. Mohri, Rostamizadeh, and Talwalkar. The MIT Press, 2012.
- Understanding Machine Learning: From Theory to Algorithms. Shalev-Shwartz and Ben- David. Cambridge University Press, 2014.
- Statistical Learning with Sparsity: The Lasso and Generalizations. Hastie, Tibshirani, and Wainwright. Chapman and Hall/CRC, 2015.
- An Introduction to Statistical Learning: with Applications in R. James, Witten, Hastie, and Tibshirani. Springer, 2017 (7th Edition). 1st Edition is in 2013.
- High-Dimensional Probability: An Introduction with Applications in Data Science. Vershynin. Cambridge University Press, 2018.
- High-Dimensional Statistics: A Non-Asymptotic Viewpoint. Wainwright. Cambridge University Press, 2019.