Week	Day	Date	Topic	Reading	Assigned	Due	Points
1	Tue	9-19-2014	Intro and Review of Probability	Chapter 2	Hmwk1	9-28-17	10
1	Thu	9-21-2014	Statistical Estimation	Chapter 17.1
2	Tue	9-26-2014	Bayes Networks	Chapter 3
2	Thu	9-28-2014	Bayes Networks (cont.), Markov Networks
3	Tue	10-3-2014	Variable Elimination	Chapter 4	Hmwk2	10-10-17	10
3	Thu	10-5-2014	Naive Bayes Classifiers, Sampling	Chapter 9
4	Tue	10-10-2014	Sampling cont.	Chapter 12
4	Thu	10-12-2014	Hmwk/Exam discussion, Learning	Chapter 17.1-17.4, Chapter 19.1, 19.2
5	Tue	10-17-2014	Mid-term 1
5	Thu	10-19-2014	Exam Review, Learning (cont.)		Hmwk 3	10-30-17	10
6	Tue	10-24-2014	No class: Jurafsky talk
6	Thu	10-26-2014	Learning (cont.) Structure Learning
7	Tue	10-31-2014	Junction Tree	Chapter 10
7	Thu	11-2-2014	Expectation-Maximization	Chapter 18
8	Tue	11-7-2014	EM (cont.), semi-supervised learning	Chapter 11	Hmwk 4	11-21-17	10
8	Thu	11-9-2014	Hmwk4, exam review, HMMs	Chapter 6
9	Tue	11-14-2014	HMMs (cont.)
9	Thu	11-16-2014	Mid-term 2
10	Tue	11-21-2014	Language Models: ngrams	Smoothing paper	Hmwk 5	12-7-17	10
10	Thu	11-23-2014	No class (Thanksgiving)
11	Tue	11-28-2014	Language Models: LSI and LDA	Gibbs for LDA
11	Thu	11-30-2014	RNNs, LSTMs