Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"

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| Tues 9/16 (Ziv) || Tues 9/16 (Wm) ||  [[10-601 Linear Regression|Linear Regression]] || ''slides will be updated''
 
| 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]] ||
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| Thurs 9/18 (Ziv) || Thurs 9/18 (Wm) ||  [[10-601 Logistic Regression|Logistic Regression]] ||
| Ziv      || William || ||
 
 
|-
 
|-
| Tues 9/23 || Tues 9/23 ||  [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William's also lecturing in Ziv's class on Mon
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| Tues 9/23 (Wm) || Tues 9/23 (Wm) ||  [[10-601 Perceptrons and Voted Perceptrons|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''
+
| Thurs 9/25 (Ziv) || Thurs 9/25 (Wm) ||  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
 
|  Tues 9/30* ||  Tues 9/30* ||  SVMs and Margin Classifiers 1 ||  Ziv's also lecturing in his class on Mon

Revision as of 17:14, 21 July 2014

This is the syllabus for Machine Learning 10-601 in Fall 2014.

Schedule

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Schedule for 10-601 in Fall 2014
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 (Ziv) Thurs 9/18 (Wm) Logistic Regression
Tues 9/23 (Wm) Tues 9/23 (Wm) The Perceptron algorithm William's also lecturing in Ziv's class on Mon
Thurs 9/25 (Ziv) Thurs 9/25 (Wm) Neural networks and Deep Belief Networks slides will be updated
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


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