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

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| Wed 8/27 (Ziv) || Tues 9/2 (Wm) ||  [[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]] ||
 
|-
 
|-
−
| Wed 9/3 (Ziv) || Thurs 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) || Thurs 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]] ||
 
|-
 
|-
 
| 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) || Thurs 9/18 (Wm) ||  [[10-601 Logistic Regression|Logistic Regression]] ||
+
| Wed 9/17 (Ziv) || Thur 9/18 (Wm) ||  [[10-601 Logistic Regression|Logistic Regression]] ||
 
|-
 
|-
 
| Mon 9/22 ('''Wm''') || Tues 9/23 (Wm) ||  [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William's also lecturing in Ziv's class on Mon
 
| Mon 9/22 ('''Wm''') || Tues 9/23 (Wm) ||  [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William's also lecturing in Ziv's class on Mon
 
|-
 
|-
−
| Wed 9/24 (Ziv) || Thurs 9/25 (Wm) ||  Neural networks and Deep Belief Networks || ''slides will be updated''
+
| Wed 9/24 (Ziv) || Thur 9/25 (Wm) ||  Neural networks and Deep Belief Networks || ''slides will be updated''
 
|-
 
|-
 
| Mon 9/29 (Ziv) ||  Tues 9/30 ('''Ziv''') ||  SVMs and Margin Classifiers 1 ||  Ziv's also lecturing in his class on Mon
 
| Mon 9/29 (Ziv) ||  Tues 9/30 ('''Ziv''') ||  SVMs and Margin Classifiers 1 ||  Ziv's also lecturing in his class on Mon
 
|-
 
|-
−
| Wed 10/1 (Ziv) || Thurs 10/2 ('''Ziv''') ||  SVMs and Margin Classifiers 2 ||  Ziv's also lecturing in his class on Wed
+
| Wed 10/1 (Ziv) || Thur 10/2 ('''Ziv''') ||  SVMs and Margin Classifiers 2 ||  Ziv's also lecturing in his class on Wed
 
|-
 
|-
−
| Tues 10/7 || Tues 10/7 ||  [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]]  ||
+
| Mon 10/6 (Ziv) || Tues 10/7 (Wm) ||  [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]]  ||
−
| Ziv      || William || ||
 
 
|-
 
|-
−
| Thus 10/9 || Thus 10/9 ||  [[10-601 PAC| PAC Learning]] ||
+
| Wed 10/8 (Ziv) || Thus 10/9 (Wm) ||  [[10-601 PAC| PAC Learning]] ||
−
| Ziv      || William || ||
 
 
|-
 
|-
−
| Tues 10/14* || Tues 10/14* ||  [[10-601 Bias-Variance|Bias-Variance Decomposition]] || William's also lecturing in Ziv's class on Mon
+
| Mon 10/13 ('''Wm''') || Tues 10/14 (Wm) ||  [[10-601 Bias-Variance|Bias-Variance Decomposition]] || William's also lecturing in Ziv's class on Mon
−
| Ziv      || William || ||
 
 
|-
 
|-
−
| Thurs 10/16 || Thurs 10/16 || [[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''
−
| Ziv      || William || ||
 
 
|-
 
|-
−
| Tues 10/21 || Tues 10/21 || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] ||
+
| Mon 10/20 (Ziv) || Tues 10/21 (Wm) || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] ||
−
| Ziv      || William || ||
 
 
|-
 
|-
−
| Thus 10/23 || Thus 10/23 || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]||
+
| Wed 10/22 (Ziv) || Thus 10/23 (Wm) || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]||
−
| Ziv      || William || ||
+
| -
−
|-
+
| Mon 10/27 (Ziv) || Tues 10/28 (Wm) || Review session || ''slides to be posted''
−
-
 
−
| 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''
 
| Thurs 10/30 || Thurs 10/30 || '''Mid-term Exam''' || ''TBA: room and/or time may be different''

Revision as of 17:22, 21 July 2014

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

Schedule

Schedule for 10-601 in Fall 2014
Lecture for 601-A Lecture for 601-B Topic Assignment/Notes
Wed 8/27 (Ziv) Tues 9/2 (Wm) Overview and Intro 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
Mon 9/15 (Ziv) Tues 9/16 (Wm) Linear Regression slides will be updated
Wed 9/17 (Ziv) Thur 9/18 (Wm) Logistic Regression
Mon 9/22 (Wm) Tues 9/23 (Wm) The Perceptron algorithm William's also lecturing in Ziv's class on Mon
Wed 9/24 (Ziv) Thur 9/25 (Wm) Neural networks and Deep Belief Networks slides will be updated
Mon 9/29 (Ziv) Tues 9/30 (Ziv) SVMs and Margin Classifiers 1 Ziv's also lecturing in his class on Mon
Wed 10/1 (Ziv) Thur 10/2 (Ziv) SVMs and Margin Classifiers 2 Ziv's also lecturing in his class on Wed
Mon 10/6 (Ziv) Tues 10/7 (Wm) Evaluating and Comparing Classifiers Experimentally
Wed 10/8 (Ziv) Thus 10/9 (Wm) PAC Learning
Mon 10/13 (Wm) Tues 10/14 (Wm) Bias-Variance Decomposition William's also lecturing in Ziv's class on Mon
Wed 10/16 (Ziv) Thur 10/16 (Wm) Ensemble Methods 1, Ensemble Methods 2 slides to be updated
Mon 10/20 (Ziv) Tues 10/21 (Wm) Unsupervised Learning: k-Means and Mixtures
Wed 10/22 (Ziv) Thus 10/23 (Wm) Unsupervised Learning: Dimensionality Reduction - Mon 10/27 (Ziv) Tues 10/28 (Wm) Review session slides to be posted
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.

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