There are two Topics in this course:

  1. Probabilistic Graphical Model
  2. Neural Networks & Deep Learning

Textbooks:

  • Bishop, Pattern Recognition and Machine Learning
  • J.Pearl, “Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Representation and Reasoning)”, Morgan Kaufmann Pub, 1998
  • I. Goodfellow, Y. Bengio, and A. Courville, “Deep Learning”, MIT Press, 2016

Probability Review

Parameter Estimation: Maximum Likelihood Estimation & Bayesian Estimation

Graphical Models (Directed)