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.
  • 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.