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====== Schedule ====== | ====== Schedule ====== | ||
- | /* | ||
- | Follow this link to view all [[https:// | ||
- | 115b6-e68b-4318-89ff-d1ecf025c0b9|lecture videos]]. | ||
- | */ | ||
===== Announcements ===== | ===== Announcements ===== | ||
- | Here is a link to all of our [[https:// | + | Sept 7: |
+ | Aug 31: Assignment 1 now includes another example. | ||
- | ===== January ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | Lecture videos are available from the Canvas site (in the menu on the left) by selecting |
- | ^ Week ^ Topic ^ Material | + | |
- | | Week 1:\\ Jan 17 - Jan 20 | Overview. Intro to machine learning. Python. | + | |
- | | Week 2:\\ Jan 23 - Jan 27 | Probability distributions and regression. | + | |
+ | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | ||
- | ===== February | + | export PATH=/ |
+ | |||
+ | /* | ||
+ | are available at this [[https:// | ||
+ | */ | ||
+ | |||
+ | |||
+ | ===== August | ||
|< 100% 10% 20% 30% 20% 20% >| | |< 100% 10% 20% 30% 20% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Jan 30 - Feb 3 | + | | Week 1:\\ Aug 21 - Aug 25 |
- | /* \\ Here are five examples of good solutions: | + | | Week 2:\\ Aug 28 - Sept 1 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. |
- | */ | + | |
- | /* | ||
- | |< 100% 20% 20% 30% 10% 20% >| | ||
- | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Feb 1 - Feb 5 | Ridge regression. Data partitioning. On-line, incremental regression. Regression with fixed nonlinearities. | ||
- | | Week 4:\\ Feb 8 - Feb 12 | Nonlinear regression with neural networks. | ||
- | | Week 5:\\ Feb 15 - Feb 19 | Autoencoders. Recurrent neural networks. | ||
- | | Week 6:\\ Feb 22 - Feb 26 | Classification, | ||
- | ===== March ===== | + | ===== September |
- | |< 100% 20% 20% 30% 10% 20% >| | + | |< 100% 10% 20% 30% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Feb 29 - Mar 5 | Classification, Introduction to Support Vector Machines. | + | | Week 3:\\ Sept 4 - Sept 8 |
- | | Week 8:\\ Mar 7 - Mar 11 | Classification with neural networks. | + | | Week 4:\\ Sept 11 - Sept 15 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. |[[http:// |
- | | Mar 14 - Mar 18 | + | | Week 5:\\ Sept 18 - Sept 22 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | [[http:// |
- | | Week 9:\\ Mar 21 - Mar 25 | Bottleneck, and deep networks. | + | | Week 6:\\ Sept 25 - Sept 29 | Negamax, with pruning. | [[http:// |
- | | Week 10:\\ Mar 28 - Apr 1 | Convolutional neural nets. Clustering. | [[http:// | + | |
- | ===== April ===== | + | ===== October |
- | |< 100% 20% 20% 30% 10% 20% >| | + | |< 100% 10% 20% 30% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Apr 4 - Apr 8 | + | | Week 7:\\ Oct 2 - Oct 6 |
- | | Week 12:\\ Apr 11 - Apr 15 | Dimensionality reduction. | + | | Week 8:\\ Oct 9 - Oct 13 |
- | | Week 13:\\ Apr 18 - Apr 22 | + | | Week 9:\\ Oct 16 - Oct 20 | |
- | | Week 14:\\ Apr 25 - Apr 29 | | [[http:// | + | | Week 10:\\ Oct 23 - Oct 27 |
+ | ===== November ===== | ||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 11:\\ Oct 30 - Nov 3 | | ||
+ | | Week 12:\\ Nov 6 - Nov 10 | | | | | ||
+ | | Week 13:\\ Nov 13 - Nov 17 | | | | | ||
+ | | Nov 20 - Nov 24 | Fall Break | | ||
+ | | Week 14:\\ Nov 27 - Dec 1 | Constraint satisfaction. Min-conflicts | ||
- | ===== May ===== | + | ===== December |
- | |< 100% 20% 20% 30% 10% 20% >| | + | |< 100% 10% 20% 30% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ May 2 - May 6 | + | | Week 15:\\ Dec 4 - Dec 8 |
+ | | Finals Week:\\ Dec 11 - Dec 15 | | | | | ||
- | | Week 16:\\ May 10 | Final Project Notebook Due. | | | Check in final project notebook by Tuesday, May 10th, at 10:00 PM. [[Final Project Report|Here is a summary]] of what is expected in your reportsl | ||
- | Selected Project Reports (in no particular order): | ||
- | |||
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- | */ | ||