Week	Day	Date	Topic	Reading	Assigned	Due	Points
1	Tue	9-20-2014	Intro and Review of Probability	Chapter 2	Hmwk1	10-3-16	10
1	Thu	9-22-2014	Statistical Estimation	Chapter 17.1
2	Tue	9-27-2014	Bayes Networks	Chapter 3
2	Thu	9-29-2014	Bayes Networks (cont.)	Chapters 4, 9
3	Tue	10-4-2014	Naive Bayes Classifiers, Markov Networks		Hmwk2	10-14-16	10
3	Thu	10-6-2014	Variable Elimination	Chapter 12
4	Tue	10-11-2014	Sampling
4	Thu	10-13-2014	Sampling cont.
5	Tue	10-18-2014	Mid-term 1
5	Thu	10-20-2014	Exam Review, Learning	Chapter 17.1-17.4, Chapter 19.1, 19.2	Hmwk 3	11-03-16	10
6	Tue	10-25-2014	Learning (cont.)
6	Thu	10-27-2014	Learning (cont.)
7	Tue	11-1-2014	Junction Tree	Chapter 10
7	Thu	11-3-2014	Structure Learning, Expectation-Maximization	Chapter 18
8	Tue	11-8-2014	Semi-supervised Learning		Hmwk 4	11-18-16	8
8	Thu	11-10-2014	HMMs	Chapter 6
9	Tue	11-15-2014	HMMs (cont.), exam review
9	Thu	11-17-2014	Mid-term 2
10	Tue	11-22-2014	Language Models: ngrams	Smoothing paper	Hmwk 5
10	Thu	11-24-2014	No class (Thanksgiving)
11	Tue	11-29-2014	Language Models: LSI and LDA	Gibbs for LDA
11	Thu	12-1-2014	RNNs, LSTMs