CS489/698 - Textbooks
There are many good references for machine learning. We will
cover material in different textbooks. The first three textbooks are
freely available online. Complementary readings in the textbooks are
assigned for every lecture in the course
schedule.
[GBC] Ian Goodfellow, Yoshua Bengio and Aaron
Courville, Deep Learning
(2016) freely available online
[HTF] Trevor Hastie, Robert Tibshirani and Jerome
Friedman, Elements of Statistical Learning (2nd edition,
2009) freely available online
[D] Hal Daume III, A
Course in Machine Learning (in progress) freely available online
[B] Christopher Bishop, Pattern Recognition and Machine Learning (2006)
[RN] Stuart Russell and
Peter Norvig, Artificial
Intelligence: A Modern Approach (3rd Edition) (2010)
[M] Kevin Murphy, Machine
Learning: A Probabilistic Perspective (2012)
[MRT] Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, Foundations
of Machine Learning (2012)
[SSBD] Shai Shalev-Shwartz, Shai Ben-David, Understanding Machine Learning: From Theory to
Algorithms (2014)