Instructor: Kevin Murphy
Recommended additional reading
Lecture notes include material borrowed from a variety of authors. Please contact me before copying.
L#  Date  Slides  Reading  Homework 

L1  Wed Sep 6 
Intro 

. 
L2  Fri Sep 8 
Intro  A chap 1  . 
L3  Mon Sep 11 
Binary classification  A 2.1, 2.4, 2.5, 2.7, 2.8 
HW1: complete
these matlab exercises
by Mon Sep 18.
The data is
here.
Clarifications

L4  Wed Sep 13 
Learning theory  A 2.2, A 2.3  . 
L5  Fri Sep 15 
Learning theory 

. 
L6  Mon Sep 18 
Bayesian concept learning 

HW2
by Mon Sep 25.
The data/code is
here.
HW2 clarifications.

L7  Wed Sep 20 
Bayesian concept learning  Refresher on probability.  . 
L8  Fri Sep 22 
Bayesian concept learning  .  . 
L9  Mon Sep 25 
Concept learning; clustering  . 
HW3
by Mon Oct 2.
The data/code is
here.
HW3 clarifications

L10  Wed Sep 27 
Modeling discrete data with Bernoulli and multinomial distributions  . 

L11  Fri Sep 29 
Modeling discrete data with Bernoulli and multinomial distributions  Optional: In praise of Bayes, Economist article, Sept 2000  . 
L12  Mon Oct 2 
Naive Bayes classifiers  Naive Bayes classifiers 
HW4 by Wed Oct 11.
Code/data is here. 
L13  Wed Oct 4 
Naive Bayes classifiers  Optional: Better Bayesian [spam] filtering, Paul Graham, Jan 2003  . 
L14  Fri Oct 6 
Markov models 

. 
L15  Mon Oct 9 
Thanksgiving  .  . 
L16  Wed Oct 11 
Markov chains  . 
HW5 due Wed Oct 18.
Code/data is here.

L17  Fri Oct 13 
Information theory  Information theory  . 
L18  Mon Oct 16 
Info theory  .  . 
L19  Wed Oct 18 
Info theory  .  No HW! 
L20  Fri Oct 20 
Review session  .  . 
L21  Mon Oct 23 
Midterm  .  . 
L22  Wed Oct 25 
Midterm postmortem  Notation used so far in class.  . 
L23  Fri Oct 27 
MCMC 

. 
L24  Mon Oct 30 
MCMC  .  hw6.pdf,
hw6Code.zip,

L25  Wed Nov 1 
MCMC  .  . 
L26  Fri Nov 3 
MRFs  MRFs  . 
L27  Mon Nov 6 
MRFs  .  . 
L28  Wed Nov 8 
Simulated annealing (hw 6)  .  . 
L29  Fri Nov 10 
Variable elimination  .  hw7.pdf,
hw7Code.zip, 
L30  Mon Nov 13 
Remembrance day holiday  .  . 
L31  Wed Nov 15 
Bayes nets  Inference in graphical models  . 
L32  Fri Nov 17 
Applications of Bayes nets  Bayes nets  hw8.pdf 
L33  Mon Nov 20 
Plates and param learning  A 3.7, Microsoft's mobile manager  . 
L34  Wed Nov 22 
Causality  Simpson's paradox (extracted from the bn.pdf file)  . 
L35  Fri Nov 24 
Gaussians  Gaussians, A 5.25.4  . 
L36  Mon Nov 27 
Snow day  .  . 
L37  Wed Nov 29 
Gaussian mixtures  Mixture models, A ch 7  . 
L38  Fri Dec 1 
Review session  .  . 
  Mon Dec 11 

3.306pm  . 