Date
|
Topic
|
Reading
|
Due
|
9/1 T
|
Intro to ML and probability review [slides]
|
Bishop, Ch 1 (up to 1.2.3) and Ch 2.1-2.2
|
Self-assessment test by Dr. Aarti Singh
|
9/3 R
|
Probability estimation [slides]
|
Bishop, Ch 1 (up to 1.2.3) and Ch 2.1-2.2
|
|
9/8 T
|
Naive Bayes classifier [slides]
|
|
|
9/10 R
|
Gaussian Naive Bayes classifier
[slides]
[note]
|
|
HW1 out
|
9/15 T
|
Logistic regression
[slides]
|
|
|
9/17 R
|
Perceptron
[slides]
|
|
|
9/22 T
|
Linear regression
[slides]
|
-
Hastie/Tibshirani/Friedman Ch. 3-Ch 3.2.1, Ch 3.2.4, Ch 3.4.1 (up to page 64)
|
HW 1 due
|
9/24 R
|
Neural network
[slides]
|
-
Mitchell Ch 4, Bishop Ch 5
|
|
9/29 T
|
k-NN, decision tree
[slides]
|
-
Mitchell Ch 3, Bishop Ch 14.4
|
|
10/1 R
|
K-means, hierarchical clustering
[slides]
|
-
Hastie et al. Ch 14.3.12, Bishop Ch 9.1
|
HW2 due
|
10/6 T
|
Mixture model
[slides]
|
|
|
10/8 R
|
Dimensionality reduction
[slides]
|
|
|
10/13 T
|
Semi-supervised learning
[slides]
|
|
HW3 due
|
10/15 R
|
Graphical model 1: model and representation
[slides]
|
|
|
10/20 T
|
Graphical model 2: inference
[slides]
|
-
Koller & Friedman Ch 9.2 (copy available on Piazza)
|
|
10/22 R
|
Graphical model 3: learning
[slides]
|
|
Project proposal due
|
10/27 T
|
Hidden Markov models: model and inference
[slides]
|
|
HW4 due
|
10/29 R
|
Hidden Markov models: inference
|
|
|
11/3 T
|
Hidden Markov models: EM algortihm for learning II
[slides]
|
|
|
11/5 R
|
Model selection, regularization
[slides] [notes]
|
-
Bishop Ch 3.1.4, Ch 14.1
-
Hastie et al. Ch 3.3-3.4
|
|
11/10 T
|
Support vector machine 1
[slides]
|
|
HW5 due
|
11/12 R
|
Support vector machine 2
[slides]
|
-
Bishop Ch 7.1, Appendix E, Ch 6.1-6.2
|
|
11/17 T
|
Midterm review
[slides]
|
|
|
11/19 R
|
Midterm
|
|
|
11/24 T
|
Boosting
[slides]
|
|
|
12/1 T
|
Learning theory
[slides]
|
|
|
12/3 R
|
Learning theory, overfitting, bias-variance trade-off
[slides]
|
|
Project mid-report due
|
12/8 T
|
Markov decision process and reinforcement learning
[slides]
|
-
Mitchell Ch 13
-
See the book chapter on MDP on Piazza
|
|
12/10 R
|
Active learning
[slides]
|
|
HW6 due
|