Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"
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'''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. | '''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. | ||
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Revision as of 16:36, 11 July 2014
This is the syllabus for Machine Learning 10-601 in Fall 2014.
Schedule
Date of lecture | Topic | Lecturer | Assignment/Notes |
---|---|---|---|
Tues 9/2 | Overview and Intro to Probability | William | |
Thurs 9/4 | Classification and K-NN | William | slides will be updated |
Tues 9/9 | Decision Trees, and Rule Learning | William | slides will be updated |
Thurs 9/11 | The Naive Bayes algorithm | William | |
Tues 9/16 | Linear Regression | William | slides will be updated |
Thurs 9/18 | Logistic Regression | William | |
(Mon +) Tues 9/23 | The Perceptron algorithm | William | William's also lecturing in Ziv's class on Mon |
Thurs 9/25 | Neural networks and Deep Belief Networks | William | slides will be updated |
(Mon +) Tues 9/30 | SVMs and Margin Classifiers 1 | Ziv | Ziv's also lecturing in his class on Mon |
(Wed +) Thurs 10/1-2 | SVMs and Margin Classifiers 2 | Ziv | Ziv's also lecturing in his class on Wed |
Tues 10/7 | Evaluating and Comparing Classifiers Experimentally | William | |
Thus 10/9 | PAC Learning | William | |
(Mon +) Tues 10/14 | Bias-Variance Decomposition | William | William's also lecturing in Ziv's class on Mon |
Thurs 10/16 | Ensemble Methods 1, Ensemble Methods 2 | William | slides to be updated |
Tues 10/21 | Unsupervised Learning: k-Means and Mixtures | Bhavana or Ziv | |
Thus 10/23 | Unsupervised Learning: Dimensionality Reduction | Bhavana or Ziv | |
Tues 10/28 | Review session | William | slides to be posted |
Thurs 10/30 | Mid-term Exam | TBA: room and/or time may be different | |
(Mon +) Tues 11/4 | Graphical Models 1 | Ziv | Ziv's also lecturing in his class on Mon |
(Wed +) Thurs 11/6 | Graphical Models 2 | Ziv | Ziv's also lecturing in his class on Wed |
(Mon +) Tues 11/11 | HMMS and Sequences | Ziv | Ziv's also lecturing in his class on Mon |
(Wed +) Thus 11/13 | Matrix Factorization and Topic Models | William | William's also lecturing in Ziv's class on Wed, slides to be updated |
(Mon +) Tues 11/18 | Network Models | William | William's also lecturing in Ziv's class on Mon |
(Wed +) Thurs 11/20 | Semi-supervised learning | William | William's also lecturing in Ziv's class on Wed |
(Mon +) Tues 11/25 | Scalable Learning and Parallelization | William | William's also lecturing in Ziv's class on Mon |
Thurs 11/27 | No class - Thanksgiving | ||
(Mon +) Tues 12/2 | Learning and NLP | William | |
(Wed +) Thurs 12/4 | Learning and Biology | 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.