Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"
From Cohen Courses
Jump to navigationJump to searchLine 5: | Line 5: | ||
{| | {| | ||
|+ 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 |
Revision as of 16:40, 11 July 2014
This is the syllabus for Machine Learning 10-601 in Fall 2014.
Schedule
Date of lecture | 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.