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====== Schedule ====== | ====== Schedule ====== | ||
- | Follow this link to view all [[https:// | + | ===== Announcements ===== |
- | == January == | + | Links to live MS Teams events: |
+ | * Lectures: [[https:// | ||
+ | * Office hours: Apoorv [[https:// | ||
+ | * Office hours: Chaitanya [[https:// | ||
+ | * Office hours: Chuck [[https:// | ||
+ | |||
- | |< 100% 20% 20% 20% 30% 10% >| | + | Recordings of lecture |
- | ^ Week ^ Topic ^ Material | + | [[https:// |
- | | Week 1:\\ Jan 19 - Jan 22 | Overview. Intro to machine learning. Python. | + | |
- | | Week 2:\\ Jan 25 - Jan 29 | Probability distributions and regression. | + | |
- | == February == | + | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: |
- | |< 100% 20% 20% 20% 30% 10% >| | + | export PATH=/ |
+ | |||
+ | This is a tentative schedule of CS440 topics for Fall, 2020. This will be updated during the summer and as the fall semester continues. | ||
+ | |||
+ | |||
+ | ===== August ===== | ||
+ | |||
+ | |< 100% 18% 20% 22% 20% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Feb 1 - Feb 5 | + | | Week 1:\\ Aug 24 - Aug 28 |
- | | Week 4:\\ Feb 8 - Feb 12 | Recurrent neural networks. | + | |
- | | Week 5:\\ Feb 15 - Feb 19 | + | |
- | | Week 6:\\ Feb 22 - Feb 26 | Classification, | + | |
- | == March == | + | ===== September ===== |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 18% 20% 22% 20% 20% > |
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 2:\\ Aug 31 - Sept 4 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. | ||
+ | | Week 3:\\ Sept 7 - Sept 11 | Informed search. A* search. Python classes, sorting, numpy arrays. | ||
+ | | Week 4:\\ Sept 14 - Sept 18 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | ||
+ | | Week 5:\\ Sept 21 - Sept 25 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | ||
+ | | Week 6:\\ Sept 28 - Oct 2 | Negamax, with pruning. Introduction to Reinforcement Learning. | ||
+ | |||
+ | ===== October ===== | ||
+ | |||
+ | |< 100% 18% 20% 22% 20% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Feb 29 - Mar 5 | Classification with neural networks. | + | | Week 7:\\ Oct 5 - Oct 9 |
- | | Week 8:\\ Mar 7 - Mar 11 | + | | Week 8:\\ Oct 12 - Oct 16 |
- | | | + | | Week 9:\\ Oct 19 - Oct 23 |
- | | Week 9:\\ Mar 21 - Mar 25 | + | | Week 10:\\ Oct 26 - Oct 30 |
- | | Week 10:\\ Mar 28 - Apr 1 | + | |
- | == April == | + | ===== November ===== |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Apr 4 - Apr 8 | + | | Week 11:\\ Nov 2 - Nov 6 |
- | | Week 12:\\ Apr 11 - Apr 15 | + | | Week 12:\\ Nov 9 - Nov 13 |
- | | Week 13:\\ Apr 18 - Apr 22 | Reinforcement learning. | + | | Week 13:\\ Nov 16 - Nov 20 |
- | | Week 14:\\ Apr 25 - Apr 29 | + | | Nov 23 - Nov 27 | Fall Recess! |
- | == May == | + | ===== December ===== |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ May 2 - May 6 | + | | Week 14:\\ Nov 30 - Dec 4 | Faster Reinforcement Learning |
+ | | Week 15:\\ Dec 7 - Dec 11 | | <!-- **Dec 3:**\\ Tom Cavey: //Image Classification and Object Detection of Things Around CSU//\\ Jason Stock: // | ||
+ | | Final Exam Week:\\ Dec 14 - Dec 18 | | ||
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