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Machine Learning
10-701/15-781, Spring 2009Machine Learning Department, School of Computer Science, Carnegie Mellon University Ziv-Bar Joseph School of Computer Science, Carnegie-Mellon University |
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Consult this page for class, recitation and exam dates, handouts, and solutions.
Course Schedule
| Date | Lecture | Readings | Handouts | NB |
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| Tue 1/13 | Intro to ML and probability | Slides | ||
| Tue 1/13 | Matlab recitation | Slides |
By Zollmann |
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| Thu 1/15 | Density estimation, classification theory | Chap 2.0 - 2.3.1 (Bishop) |
Slides |
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| Tue 1/20 | Classification | Chap 1.5 and 2.5 (Bishop) |
Slides Problem set 1 Data file 1 for PS 1 Data file 2 for PS 1 |
PS1 out |
| Tue 1/20 | Distributions recitation | Slides Latex guide Board work |
By Ray |
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| Thu 1/22 | Naive bayes classifier, Linear
regression |
Chap 1.5, 3.0 - 3.3 (Bishop) |
Slide set
1, Slide set 2 |
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| Tue 1/27 | Logistic regression |
Chap 4.3 (Bishop) |
Slides |
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| Tue 1/27 | Linear regression recitation |
Slides |
By Ray |
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| Thu 1/29 | Decision trees | Slides PS2 Dataset for PS2 |
PS2 out |
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| Tue 2/3 | Neural networks | Chap 4 (Mitchell) |
Annotated slides |
Lecture by Tom Mitchell. PS1 due |
| Tue 2/3 | Estimation & regression recitation | Slides |
By Zollmann |
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| Thu 2/5 | Boosting |
Chapter 14.3 (Bishop) |
Annotated slides |
Lecture by Eric Xing. |
| Tue 2/10 | Learning theory 1 |
Chapter 7 (Mitchell) |
Annotated slides |
Lecture by Tom Mitchell. |
| Tue 2/10 | Decision trees & confidence interval recitation |
Slides |
By Zollmann |
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| Thu 2/12 | Learning theory 2 |
Chapter 7 (Mitchell) |
Annotated slides PS3 MAT file for PS3 |
Lecture by Tom Mitchell. PS2 due, PS3 out |
| Tue 2/17 | Support vector machine | Chapter 7.1 (Bishop) |
Slides |
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| Tue 2/17 | Error bounds, SVM recitation | Slides |
By Li |
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| Thu 2/19 | SVM, Bayesian Networks | PS1 solutions out here | ||
| Tue 2/24 | Bayesian Network | Chap 8.1, 8.2.2 (Bishop) |
Slides |
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| Tue 2/24 | Graphical models recitation | Slides |
By Li |
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| Thu 2/26 | Hidden Markov Model | Chap 13 - 13.2 (Bishop) |
Slides |
PS3 due, PS2 solns out here |
| Tue 3/3 | Hidden Markov Model | Slides |
PS3 solns out here |
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| Tue 3/3 | Midterm review | By Ziv |
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| Thu 3/5 | Midterm exam | Solutions out here |
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| Tue 3/10 | Spring Break | |||
| Thu 3/12 | Spring Break | |||
| Tue 3/17 |
Undirected models | Slides |
Lecture by Eric
Xing Term project proposals due |
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| Tue 3/17 |
HMM recitation | Slides |
By Li | |
| Thu 3/19 | ML in the industry |
Slides Problem Set 4 |
Lecture by Tim
Graettinger PS4 out |
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| Tue 3/24 | Markov Decision Process | Demo : Link | Slides |
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| Tue 3/24 | BN recitation | Boardwork only |
By Zollmann |
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| Thu 3/26 |
Reinforcement learning | Slides |
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| Tue 3/31 | Hierarchical Clustering, K-means | Chap 9.0 - 9.2 (Bishop) |
Slides |
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| Tue 3/31 | GM recitation | Boardwork only |
By Li |
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| Thu 4/2 |
Gaussian Mixtures |
PS4 due |
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| Tue 4/7 |
Graph Clustering, Semi-supervised Learning | Slides Proof Tutorial PS5 |
Term project progress report due PS5 out |
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| Tue 4/7 |
Markov processes, and sampling recitation | Boardwork |
By Ray |
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| Thu 4/9 | Principal component analysis and singular value decomposition | Slides |
Lecture by Andreas Zollmann |
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| Tue 4/14 |
Model and feature selection |
Slides |
Lecture by Pradipta Ray |
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| Tue 4/14 |
MDP recitation |
Boardwork only |
By Ray |
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| Thu 4/16 | No class |
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| Tue 4/21 | Text classification analysis | Slides |
Lecture by Tom Mitchell PS5 due, PS4 solns out here |
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| Thu 4/23 |
No class |
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| Tue 4/28 | Computational Biology |
Slides |
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| Tue 4/28 | Poster session |
Newell Simon Hall Atrium 3pm - 6pm |
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| Thu 4/30 | Semi-supervised Learning | Slides |
PS5 solutions out. Sample soln here (courtesy Javier Hernandez) with annotations by Pradipta |
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| Thu 4/30 | End term review session | 06:00 pm onwards, loc WeH 5409 |
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| Tue 5/5 | End term exams |
Loc: WeH 7500 08:30am - 11:30am Solutions are here |
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| Thu 5/7 | No class | Final report due |