Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"
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! ''Notes''/Assignment | ! ''Notes''/Assignment | ||
|- | |- | ||
− | | Wed 8/27 (Ziv) || Tues 9/2 (Wm) || [[10-601 Introduction to Probability|Course Overview and Introduction to Probability]] || | + | | Wed 8/27 (Ziv) || Tues 9/2 (Wm) || [[10-601 Introduction to Probability|Course Overview and Introduction to Probability]] || |
|- | |- | ||
| Wed 9/3 (Ziv) || Thur 9/4 (Wm) || [[10-601 K-NN And Trees|Classification and K-NN]] || ''slides will be updated'' | | Wed 9/3 (Ziv) || Thur 9/4 (Wm) || [[10-601 K-NN And Trees|Classification and K-NN]] || ''slides will be updated'' | ||
|- | |- | ||
− | | Mon 9/8 (Ziv) || Tues 9/9 (Wm) || | [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || ''slides will be updated'' | + | | Mon 9/8 (Ziv) || Tues 9/9 (Wm) || | [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || ''slides will be updated'' |
|- | |- | ||
− | | Wed 9/10 (Ziv) || Thur 9/11 (Wm) || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || | + | | Wed 9/10 (Ziv) || Thur 9/11 (Wm) || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || HW1: KNN and Decision Trees (Worksheet) - due 9/18 |
|- | |- | ||
− | | Mon 9/15 (Ziv) || Tues 9/16 (Wm) || [[10-601 Linear Regression|Linear Regression]] || ''slides will be updated'' | + | | Mon 9/15 (Ziv) || Tues 9/16 (Wm) || [[10-601 Linear Regression|Linear Regression]] || ''slides will be updated'' |
|- | |- | ||
− | | Wed 9/17 (Ziv) || Thur 9/18 (Wm) || [[10-601 Logistic Regression|Logistic Regression]] || | + | | Wed 9/17 (Ziv) || Thur 9/18 (Wm) || [[10-601 Logistic Regression|Logistic Regression]] || HW2: Naive Bayes, Linear Regression (Matlab Programming) - due 9/25 |
|- | |- | ||
− | | Mon 9/22 ('''Wm''') || Tues 9/23 (Wm) || [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || | + | | Mon 9/22 ('''Wm''') || Tues 9/23 (Wm) || [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || |
|- | |- | ||
− | | Wed 9/24 (Ziv) || Thur 9/25 (Wm) || Neural networks and Deep Belief Networks || | + | | Wed 9/24 (Ziv) || Thur 9/25 (Wm) || Neural networks and Deep Belief Networks || HW3: Logistic Regression, Neural networks (Matlab Programming) - due 10/9 |
|- | |- | ||
− | | Mon 9/29 (Ziv) || Tues 9/30 ('''Ziv''') || SVMs and Margin Classifiers 1 || | + | | Mon 9/29 (Ziv) || Tues 9/30 ('''Ziv''') || SVMs and Margin Classifiers 1 || |
|- | |- | ||
| Wed 10/1 (Ziv) || Thur 10/2 ('''Ziv''') || SVMs and Margin Classifiers 2 || | | Wed 10/1 (Ziv) || Thur 10/2 ('''Ziv''') || SVMs and Margin Classifiers 2 || | ||
|- | |- | ||
− | | Mon 10/6 (Ziv) || Tues 10/7 (Wm) || [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]] || | + | | Mon 10/6 (Ziv) || Tues 10/7 (Wm) || [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]] || |
|- | |- | ||
− | | Wed 10/8 (Ziv) || Thus 10/9 (Wm) || [[10-601 PAC| PAC Learning]] || ''wiki page to be updated'' | + | | Wed 10/8 (Ziv) || Thus 10/9 (Wm) || [[10-601 PAC| PAC Learning]] || ''wiki page to be updated'' / HW4: SVM, Comparing classifiers (Experiments with Weka) - due 10/16 |
|- | |- | ||
− | | Mon 10/13 ('''Wm''') || Tues 10/14 (Wm) || [[10-601 Bias-Variance|Bias-Variance Decomposition]] || ''wiki page to be updated'' | + | | Mon 10/13 ('''Wm''') || Tues 10/14 (Wm) || [[10-601 Bias-Variance|Bias-Variance Decomposition]] || ''wiki page to be updated'' |
|- | |- | ||
− | | Wed 10/16 (Ziv) || Thur 10/16 (Wm) || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| ''slides to be updated'' | + | | Wed 10/16 (Ziv) || Thur 10/16 (Wm) || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| ''slides to be updated'' / HW5: Pac-learning (worksheet) - die 10/27 |
|- | |- | ||
− | | Mon 10/20 (Ziv) || Tues 10/21 (Wm) || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] || ''potential guest lecture'' | + | | Mon 10/20 (Ziv) || Tues 10/21 (Wm) || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] || ''potential guest lecture'' |
|- | |- | ||
| Wed 10/22 (Ziv) || Thur 10/23 (Wm) || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]|| | | Wed 10/22 (Ziv) || Thur 10/23 (Wm) || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]|| | ||
|- | |- | ||
− | | Mon 10/27 (Ziv) || Tues 10/28 (Wm) || Review session || ''slides to be posted'' Practice exam distributed | + | | Mon 10/27 (Ziv) || Tues 10/28 (Wm) || Review session || ''slides to be posted'' Practice exam distributed |
|- | |- | ||
| Thurs 10/30 || Thur 10/30 || '''Mid-term Exam''' || ''TBA: room and/or time may be different'' | | Thurs 10/30 || Thur 10/30 || '''Mid-term Exam''' || ''TBA: room and/or time may be different'' | ||
|- | |- | ||
− | | Mon 11/3 (Ziv) || Tues 11/4 ('''Ziv''') || [[10-601 GM1| Graphical Models 1]] || ''wiki to be updated'' | + | | Mon 11/3 (Ziv) || Tues 11/4 ('''Ziv''') || [[10-601 GM1| Graphical Models 1]] || ''wiki to be updated'' / HW6: unsupervised learning (programming) - due 11/10 |
|- | |- | ||
| Wed 11/5 (Ziv) || Thur 11/6 ('''Ziv''') || [[10-601 GM2| Graphical Models 2]] || ''wiki to be updated'' | | Wed 11/5 (Ziv) || Thur 11/6 ('''Ziv''') || [[10-601 GM2| Graphical Models 2]] || ''wiki to be updated'' | ||
|- | |- | ||
− | | Mon 11/10 (Ziv) || Tues 11/11 ('''Ziv''') || [[10-601 Sequences|HMMS and Sequences]] || | + | | Mon 11/10 (Ziv) || Tues 11/11 ('''Ziv''') || [[10-601 Sequences|HMMS and Sequences]] || HW7: HMMS and Graphical Models (worksheet) / due 11-17 |
|- | |- | ||
| Wed 11/13 ('''Wm''') || Thur 11/13 (Wm) || [[10-601 Topic Models|Matrix Factorization and Topic Models]]|| ''slides to be updated'' | | Wed 11/13 ('''Wm''') || Thur 11/13 (Wm) || [[10-601 Topic Models|Matrix Factorization and Topic Models]]|| ''slides to be updated'' | ||
|- | |- | ||
− | | Mon 11/17 ('''Wm''') || Tues 11/18 (Wm) || [[10-601 Network Models| Network Models]] || HW10: HMM/Topic models (worksheet, experiments with LDA code) | + | | Mon 11/17 ('''Wm''') || Tues 11/18 (Wm) || [[10-601 Network Models| Network Models]] || HW10: HMM/Topic models (worksheet, experiments with LDA code) - due 11/24 |
|- | |- | ||
| Wed 11/19 ('''Wm''') || Thur 11/20 (Wm)|| Semi-supervised learning || ''possible guest lecture'' | | Wed 11/19 ('''Wm''') || Thur 11/20 (Wm)|| Semi-supervised learning || ''possible guest lecture'' |
Revision as of 11:31, 5 August 2014
This is the syllabus for Machine Learning 10-601 in Fall 2014.
Schedule
Lecture for 601-A | Lecture for 601-B | Topic | Notes/Assignment |
---|---|---|---|
Wed 8/27 (Ziv) | Tues 9/2 (Wm) | Course Overview and Introduction to Probability | |
Wed 9/3 (Ziv) | Thur 9/4 (Wm) | Classification and K-NN | slides will be updated |
Mon 9/8 (Ziv) | Tues 9/9 (Wm) | Decision Trees, and Rule Learning | slides will be updated |
Wed 9/10 (Ziv) | Thur 9/11 (Wm) | The Naive Bayes algorithm | HW1: KNN and Decision Trees (Worksheet) - due 9/18 |
Mon 9/15 (Ziv) | Tues 9/16 (Wm) | Linear Regression | slides will be updated |
Wed 9/17 (Ziv) | Thur 9/18 (Wm) | Logistic Regression | HW2: Naive Bayes, Linear Regression (Matlab Programming) - due 9/25 |
Mon 9/22 (Wm) | Tues 9/23 (Wm) | The Perceptron algorithm | |
Wed 9/24 (Ziv) | Thur 9/25 (Wm) | Neural networks and Deep Belief Networks | HW3: Logistic Regression, Neural networks (Matlab Programming) - due 10/9 |
Mon 9/29 (Ziv) | Tues 9/30 (Ziv) | SVMs and Margin Classifiers 1 | |
Wed 10/1 (Ziv) | Thur 10/2 (Ziv) | SVMs and Margin Classifiers 2 | |
Mon 10/6 (Ziv) | Tues 10/7 (Wm) | Evaluating and Comparing Classifiers Experimentally | |
Wed 10/8 (Ziv) | Thus 10/9 (Wm) | PAC Learning | wiki page to be updated / HW4: SVM, Comparing classifiers (Experiments with Weka) - due 10/16 |
Mon 10/13 (Wm) | Tues 10/14 (Wm) | Bias-Variance Decomposition | wiki page to be updated |
Wed 10/16 (Ziv) | Thur 10/16 (Wm) | Ensemble Methods 1, Ensemble Methods 2 | slides to be updated / HW5: Pac-learning (worksheet) - die 10/27 |
Mon 10/20 (Ziv) | Tues 10/21 (Wm) | Unsupervised Learning: k-Means and Mixtures | potential guest lecture |
Wed 10/22 (Ziv) | Thur 10/23 (Wm) | Unsupervised Learning: Dimensionality Reduction | |
Mon 10/27 (Ziv) | Tues 10/28 (Wm) | Review session | slides to be posted Practice exam distributed |
Thurs 10/30 | Thur 10/30 | Mid-term Exam | TBA: room and/or time may be different |
Mon 11/3 (Ziv) | Tues 11/4 (Ziv) | Graphical Models 1 | wiki to be updated / HW6: unsupervised learning (programming) - due 11/10 |
Wed 11/5 (Ziv) | Thur 11/6 (Ziv) | Graphical Models 2 | wiki to be updated |
Mon 11/10 (Ziv) | Tues 11/11 (Ziv) | HMMS and Sequences | HW7: HMMS and Graphical Models (worksheet) / due 11-17 |
Wed 11/13 (Wm) | Thur 11/13 (Wm) | Matrix Factorization and Topic Models | slides to be updated |
Mon 11/17 (Wm) | Tues 11/18 (Wm) | Network Models | HW10: HMM/Topic models (worksheet, experiments with LDA code) - due 11/24 |
Wed 11/19 (Wm) | Thur 11/20 (Wm) | Semi-supervised learning | possible guest lecture |
Mon 11/24 (Wm) | Tues 11/25 (Wm) | Scalable Learning and Parallelization | Project milestone 1 (Evaluating/reporting on Weka classifiers) |
Wed 11/26 | Thur 11/27 | No class - Thanksgiving | |
Tues 12/2 (Wm) | Tues 12/2 (Wm) | Learning and NLP | slides to be updated / Project milestone 2 (Combining Weka classifiers) |
Wed 12/3 (Ziv) | Thurs 12/4 (Ziv) | Learning and Biology | |
Mon 12/8 | Project due (Final experiments and writeup) |
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