Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"
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! Assignment/Notes | ! Assignment/Notes | ||
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| − | | Wed 8/27 || Tues 9/2|| [[10-601 Introduction to Probability|Overview and Intro to Probability]] || | + | | Wed 8/27 (Ziv) || Tues 9/2 (Wm) || [[10-601 Introduction to Probability|Overview and Intro to Probability]] || |
|- | |- | ||
| − | | Ziv | + | | Thurs 9/4 (Ziv) || Thurs 9/4 (Wm) || [[10-601 K-NN And Trees|Classification and K-NN]] || ''slides will be updated'' |
| + | |- | ||
| + | | Tues 9/9 (Ziv) || Tues 9/9 (Wm) || | [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || ''slides will be updated'' | ||
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| − | | Thurs 9/ | + | | Thurs 9/11 (Ziv) || Thurs 9/11 (Wm) || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || |
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| + | | Tues 9/16 (Ziv) || Tues 9/16 (Wm) || [[10-601 Linear Regression|Linear Regression]] || ''slides will be updated'' | ||
| + | |- | ||
| Thurs 9/18 || Thurs 9/18 || [[10-601 Logistic Regression|Logistic Regression]] || | | Thurs 9/18 || Thurs 9/18 || [[10-601 Logistic Regression|Logistic Regression]] || | ||
| Ziv || William || || | | Ziv || William || || | ||
Revision as of 17:13, 21 July 2014
This is the syllabus for Machine Learning 10-601 in Fall 2014.
Schedule
-| 601A | 601B | Topic | Assignment/Notes | |||||
|---|---|---|---|---|---|---|---|---|
| Wed 8/27 (Ziv) | Tues 9/2 (Wm) | Overview and Intro to Probability | ||||||
| Thurs 9/4 (Ziv) | Thurs 9/4 (Wm) | Classification and K-NN | slides will be updated | |||||
| Tues 9/9 (Ziv) | Tues 9/9 (Wm) | Decision Trees, and Rule Learning | slides will be updated | |||||
| Thurs 9/11 (Ziv) | Thurs 9/11 (Wm) | The Naive Bayes algorithm | ||||||
| Tues 9/16 (Ziv) | Tues 9/16 (Wm) | Linear Regression | slides will be updated | |||||
| Thurs 9/18 | Thurs 9/18 | Logistic Regression | Ziv | William | ||||
| Tues 9/23 | Tues 9/23 | The Perceptron algorithm | William's also lecturing in Ziv's class on Mon | Ziv | William | |||
| Thurs 9/25 | Thurs 9/25 | Neural networks and Deep Belief Networks | slides will be updated | Ziv | William | |||
| Tues 9/30* | Tues 9/30* | SVMs and Margin Classifiers 1 | Ziv's also lecturing in his class on Mon | Ziv | William | |||
| Thurs 10/2* | Thurs 10/2* | SVMs and Margin Classifiers 2 | Ziv's also lecturing in his class on Wed | Ziv | William | |||
| Tues 10/7 | Tues 10/7 | Evaluating and Comparing Classifiers Experimentally | Ziv | William | ||||
| Thus 10/9 | Thus 10/9 | PAC Learning | Ziv | William | ||||
| Tues 10/14* | Tues 10/14* | Bias-Variance Decomposition | William's also lecturing in Ziv's class on Mon | Ziv | William | |||
| Thurs 10/16 | Thurs 10/16 | Ensemble Methods 1, Ensemble Methods 2 | slides to be updated | Ziv | William | |||
| Tues 10/21 | Tues 10/21 | Unsupervised Learning: k-Means and Mixtures | Ziv | William | ||||
| Thus 10/23 | Thus 10/23 | Unsupervised Learning: Dimensionality Reduction | Ziv | William | ||||
| Tues 10/28 | Tues 10/28 | Review session | slides to be posted | Ziv | William | |||
| Thurs 10/30 | Thurs 10/30 | Mid-term Exam | TBA: room and/or time may be different | Ziv | William | |||
| Tues 11/4* | Tues 11/4* | Graphical Models 1 | Ziv's also lecturing in his class on Mon | Ziv | William | |||
| Thurs 11/6* | Thurs 11/6* | Graphical Models 2 | Ziv's also lecturing in his class on Wed | Ziv | William | |||
| Tues 11/11* | Tues 11/11* | HMMS and Sequences | Ziv's also lecturing in his class on Mon | Ziv | William | |||
| Thus 11/13* | Thus 11/13* | Matrix Factorization and Topic Models | William's also lecturing in Ziv's class on Wed, slides to be updated | Ziv | William | |||
| Tues 11/18* | Tues 11/18* | Network Models | William's also lecturing in Ziv's class on Mon | Ziv | William | |||
| Thurs 11/20* | Thurs 11/20* | Semi-supervised learning | William's also lecturing in Ziv's class on Wed | Ziv | William | |||
| Tues 11/25* | Tues 11/25* | Scalable Learning and Parallelization | William's also lecturing in Ziv's class on Mon | Ziv | William | |||
| Thurs 11/27 | Thurs 11/27 | No class - Thanksgiving | ||||||
| Tues 12/2* | Tues 12/2* | Learning and NLP | Ziv | William | ||||
| Thurs 12/4 | Thurs 12/4 | Learning and Biology | Ziv | William |
To other instructors: if you'd like to use any of the materials found here, you're absolutely welcome to do so, but please acknowledge their ultimate source somewhere.
