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