Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"
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{| | {| | ||
|+ Schedule for 10-601 in Fall 2013 | |+ Schedule for 10-601 in Fall 2013 | ||
− | ! Date of lecture | + | ! Date of lecture | Alternate |
! Topic | ! Topic | ||
! Lecturer | ! Lecturer | ||
! Assignment/Notes | ! Assignment/Notes | ||
|- | |- | ||
− | | Tues 9/2|| [[10-601 Introduction to Probability|Overview and Intro to Probability]] || William|| | + | | Tues 9/2|| || [[10-601 Introduction to Probability|Overview and Intro to Probability]] || William|| |
|- | |- | ||
− | | Thurs 9/4|| [[10-601 K-NN And Trees|Classification and K-NN]] || William || ''slides will be updated'' | + | | Thurs 9/4|| || [[10-601 K-NN And Trees|Classification and K-NN]] || William || ''slides will be updated'' |
|- | |- | ||
− | | Tues 9/9 || [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || William || ''slides will be updated'' | + | | Tues 9/9 || || [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || William || ''slides will be updated'' |
|- | |- | ||
− | | Thurs 9/11 || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || William || | + | | Thurs 9/11 || || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || William || |
|- | |- | ||
− | | Tues 9/16 || [[10-601 Linear Regression|Linear Regression]] || William || ''slides will be updated'' | + | | Tues 9/16 || || [[10-601 Linear Regression|Linear Regression]] || William || ''slides will be updated'' |
|- | |- | ||
− | | Thurs 9/18 || [[10-601 Logistic Regression|Logistic Regression]] || William || | + | | Thurs 9/18 || || [[10-601 Logistic Regression|Logistic Regression]] || William || |
|- | |- | ||
− | | | + | | Tues 9/23 || || [[10-601 Perceptrons and Voted Perceptrons|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'' | + | | Thurs 9/25 || || Neural networks and Deep Belief Networks || William || ''slides will be updated'' |
|- | |- | ||
− | | | + | | Tues 9/30 || Mon || SVMs and Margin Classifiers 1 || Ziv || Ziv's also lecturing in his class on Mon |
|- | |- | ||
− | | | + | | Thurs 10/1-2 || Wed || SVMs and Margin Classifiers 2 || Ziv || Ziv's also lecturing in his class on Wed |
|- | |- | ||
− | | Tues 10/7 || [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]] || William || | + | | Tues 10/7 || || [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]] || William || |
|- | |- | ||
− | | Thus 10/9 || [[10-601 PAC| PAC Learning]] || William || | + | | Thus 10/9 || || [[10-601 PAC| PAC Learning]] || William || |
|- | |- | ||
− | | | + | | Tues 10/14 || Mon || [[10-601 Bias-Variance|Bias-Variance Decomposition]] || William || William's also lecturing in Ziv's class on Mon |
|- | |- | ||
| Thurs 10/16 || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| William || ''slides to be updated'' | | Thurs 10/16 || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| William || ''slides to be updated'' | ||
Line 46: | Line 46: | ||
| Thurs 10/30 || '''Mid-term Exam''' || || ''TBA: room and/or time may be different'' | | Thurs 10/30 || '''Mid-term Exam''' || || ''TBA: room and/or time may be different'' | ||
|- | |- | ||
− | | | + | | Tues 11/4 || Mon || [[10-601 GM1| Graphical Models 1]] || Ziv || Ziv's also lecturing in his class on Mon |
|- | |- | ||
− | | | + | | Thurs 11/6 || Wed || [[10-601 GM2| Graphical Models 2]] || Ziv || Ziv's also lecturing in his class on Wed |
|- | |- | ||
− | | | + | | Tues 11/11 || Mon || [[10-601 Sequences|HMMS and Sequences]] || Ziv || Ziv's also lecturing in his class on Mon |
|- | |- | ||
− | | | + | | Thus 11/13 || Wed || [[10-601 Topic Models|Matrix Factorization and Topic Models]]|| William || William's also lecturing in Ziv's class on Wed, ''slides to be updated'' |
|- | |- | ||
− | | | + | | Tues 11/18 || Mon || [[10-601 Network Models| Network Models]] || William || William's also lecturing in Ziv's class on Mon |
|- | |- | ||
− | | | + | | Thurs 11/20 || Wed || Semi-supervised learning || William || William's also lecturing in Ziv's class on Wed |
|- | |- | ||
− | | | + | | Tues 11/25 || Mon || [[10-601 Big Data|Scalable Learning and Parallelization]] || William || William's also lecturing in Ziv's class on Mon |
|- | |- | ||
− | | Thurs 11/27 || ''No class - Thanksgiving'' || | + | | Thurs 11/27 || || ''No class - Thanksgiving'' || |
|- | |- | ||
− | | | + | | Tues 12/2 || Mon || Learning and NLP || William || |
|- | |- | ||
− | | | + | | Thurs 12/4 || Wed || 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. | '''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. |
Revision as of 16:40, 11 July 2014
This is the syllabus for Machine Learning 10-601 in Fall 2014.
Schedule
Alternate | 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 | ||
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 | |
Tues 9/30 | Mon | SVMs and Margin Classifiers 1 | Ziv | Ziv's also lecturing in his class on Mon |
Thurs 10/1-2 | Wed | 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 | ||
Tues 10/14 | Mon | 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 | ||
Tues 11/4 | Mon | Graphical Models 1 | Ziv | Ziv's also lecturing in his class on Mon |
Thurs 11/6 | Wed | Graphical Models 2 | Ziv | Ziv's also lecturing in his class on Wed |
Tues 11/11 | Mon | HMMS and Sequences | Ziv | Ziv's also lecturing in his class on Mon |
Thus 11/13 | Wed | Matrix Factorization and Topic Models | William | William's also lecturing in Ziv's class on Wed, slides to be updated |
Tues 11/18 | Mon | Network Models | William | William's also lecturing in Ziv's class on Mon |
Thurs 11/20 | Wed | Semi-supervised learning | William | William's also lecturing in Ziv's class on Wed |
Tues 11/25 | Mon | Scalable Learning and Parallelization | William | William's also lecturing in Ziv's class on Mon |
Thurs 11/27 | No class - Thanksgiving | |||
Tues 12/2 | Mon | Learning and NLP | William | |
Thurs 12/4 | Wed | 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.