Difference between revisions of "Syllabus for Machine Learning 10-601B in Spring 2016"
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| W 2/17 || [[10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification | Generalization and Overfitting: Sample Complexity Results for Supervised Classification]] || Nina || [http://curtis.ml.cmu.edu/w/courses/images/2/25/10601-Homework-4.pdf HW4: SVM, ANN, Boosting] || Han, Tianshu | | W 2/17 || [[10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification | Generalization and Overfitting: Sample Complexity Results for Supervised Classification]] || Nina || [http://curtis.ml.cmu.edu/w/courses/images/2/25/10601-Homework-4.pdf HW4: SVM, ANN, Boosting] || Han, Tianshu | ||
|- | |- | ||
− | | M 2/22 || [[10-601B | + | | M 2/22 || [[10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification 2 | Generalization and Overfitting: Sample Complexity Results for Supervised Classification 2]] || Nina || || |
|- | |- | ||
| W 2/24|| Midterm Review || Nina || || | | W 2/24|| Midterm Review || Nina || || |
Revision as of 10:50, 23 February 2016
This is the syllabus for Machine Learning 10-601 in Spring 2016.
Schedule
Teaching team only: also see the Google Doc Spreadsheet. Students should not try and decipher the scribbles and planning notes on this gdoc - use the schedule below.
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.
Note from William to William and Nina: there's a copy of the old draft, with William's slides and notes, here