Difference between revisions of "Syllabus for Machine Learning 10-601B in Spring 2016"
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| 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 || || | | 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|| [[10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification 3 | Generalization and Overfitting: Sample Complexity Results for Supervised Classification 3]] and Midterm Review || Nina || || |
|- | |- | ||
| M 2/29 ||colspan="4"| ''Midterm exam'' | | M 2/29 ||colspan="4"| ''Midterm exam'' |
Revision as of 21:32, 26 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