Instructor: Jayadev Acharya, 304 Rhodes Hall
Office hours: MoTh 1500-1600 hours, Location: 310 Rhodes Hall
(Starting 1/30/17)
Week | Topic | References | |
1 | Introduction, Decision trees | Mitchell Ch. 3, CIML Ch. 1 | |
2 | Naive Bayes | Mitchell 6.9-6.10; Murphy 3.5 | |
3 | Perceptron | Mitchell Ch. 4, CIML Ch. 4 | |
4, | Regression, regularization | ESL 3.2, 3.2.2, 3.4, 3.4.2, notes-cuny | |
5, 6 | SVM, Kernel trick | Bishop Ch. 7.1,Andrew-Ng Notes | |
7 | Nearest neighbor methods | Mitchell Ch 8 | |
8 | Bagging, boosting | notes-breiman, tutorial-boosting | |
9 | Neural Networks | Mitchell Ch 4. | |
10 | HMM, Viterbi algorithm | Rabiner-Tutorial, Murphy Ch. 15.1-15.3 | |
11 | Dimensionality reduction: PCA, JL transforms | dasgupta-gupta-jl, poczos-notes, parr-notes | |
12 | k-means, EM algorithm | Bishop Ch. 9 | |
13 | Learning Theory | Mitchell Ch. 7 |