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]] || HW1: Probability (Worksheet)
+
| 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'' / HW2: Decision Tree (Worksheet)
+
| 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'' / HW3: Naive Bayes (Matlab Programming)
+
| 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]] || HW4: Logistic Regression (Matlab Programming)
+
| 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 || ''slides will be updated''
+
| 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 ||  HW5: Neural nets (worksheet)
+
| 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]]  || HW6: Comparing classifiers (Experiments with Weka)
+
| 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'' / HW7: Pac-learning (worksheet)
+
| 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'' / HW8: k-means (programming)
+
| 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]] || HW9: Graphical Models (worksheet)
+
|  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

Schedule for 10-601 in Fall 2014
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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