Machine Learning

CS 5350/6350, DS 4350, Spring 2024

Probabilistic Learning

In this lecture, we will look at probabilistic criteria for defining what it means to learn. Specifically, we will see maximum a posteriori and maximum likelihood learning criteria with examples.


  • Chapter 6 of Tom Mitchell’s book

  • Chapter 7 of A Course in Machine Learning by Hal Daume

  • Chapters 2 and 3 of Pattern Classification by Duda, Hart and Stork