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Course Materials - Spring 2025

ML801: Foundations and Advanced Topics in Machine Learning

ML803: Advanced Probabilistic and Statistical Inference 

 TB = Textbook or Required reading                     REF = Reference or supplemental reading

Type .................... Title

eBook

Print  

Call Number 
G. Casella, and R. L. Berger, Statistical Inference, 2nd ed. Cengage Learning, 2001.

NA

 

Yes QA276 .C37 2002 
D. Koller  and N. Friedman, Probabilistic Graphical Models: Principles and Techniques. MIT Press, 2009 ProQuest Yes QA279.5.K65 2009
C. Bishop, Pattern Recognition and Machine Learning. Berlin: Springer-Verlag, 2006. Author copy Yes Q327.B52 2009
K. Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012. ProQuest Yes QA278.8 .W37 2006
D. Barber, Bayesian reasoning and machine learning. Cambridge University Press. 2012.

Open Access

Yes QA267 .B347 2012
D. Koller and N. Friedman, Probabilistic Graphical Models: Principles and Techniques,  MIT Press. 2009. ProQuest Yes QA279.5 .K65 2009
D. J. C. MacKay, Information Theory, Inference and Learning Algorithms, Cambridge University Press. 2003. Open Access Yes Q360 .M23 2003
S. Nowozin and C. Lampert, Structured Learning and Prediction in Computer Vision, Foundations and Trends in Computer Graphics and Vision Vol. 6, Nos. 3–4 (2010) 185–365, 2011. Open Access Yes TA1634 .N6 2011