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- | ====== Schedule ====== | + | ===== Schedule ====== |
===== Announcements ===== | ===== Announcements ===== | ||
+ | Links to live MS Teams events: | ||
+ | * Lectures: [[https:// | ||
+ | * Office hours: Apoorv [[https:// | ||
+ | * Office hours: Chaitanya [[https:// | ||
+ | * Office hours: Chuck [[https:// | ||
+ | |||
- | Lecture | + | Recordings of lecture and office hour videos are available from the Home page of our |
+ | [[https:// | ||
To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | ||
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export PATH=/ | 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. | |
- | This is a tentative schedule of CS440 topics for Fall, 2018. This will be updated during the summer and as the fall semester continues. | + | |
===== August ===== | ===== August ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 1:\\ Aug 20 - Aug 24 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. | + | | Week 1:\\ Aug 24 - Aug 28 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. |
- | | Week 2:\\ Aug 27 - Aug 31 | + | |
===== September ===== | ===== September ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
- | ^ Week ^ Topic ^ Material | + | ^ Week ^ Topic ^ Material |
- | | Week 3:\\ Sept 4 - Sept 7\\ No class on the Sept 3 University Holiday | + | | Week 2:\\ Aug 31 - Sept 4 | Help with A1.\\ Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. |
- | | Week 4:\\ Sept 10 - Sept 14 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | + | | Week 3:\\ Sept 7 - Sept 11 | Informed search. A* search. Python classes, sorting, numpy arrays. |
- | | Week 5:\\ Sept 17 - Sept 21 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | + | | Week 4:\\ Sept 14 - Sept 18 | A* optimality, admissible heuristics |
- | | Week 6:\\ Sept 24 - Sept 28 | Negamax, with pruning. | [[http:// | + | | Week 5:\\ Sept 21 - Sept 25 | Effective branching factor.\\ Local search and optimization. |
+ | | Week 6:\\ Sept 28 - Oct 2 | Negamax, with pruning. | ||
===== October ===== | ===== October ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Oct 2 - Oct 6 | + | | Week 7:\\ Oct 5 - Oct 9\\ <color red>Oct 8 Lecture will not meet, but recording will be available.</ |
- | | Week 8:\\ Oct 9 - Oct 13 | + | | Week 8:\\ Oct 12 - Oct 16 |
- | | Week 9:\\ Oct 16 - Oct 20 | + | | Week 9:\\ Oct 19 - Oct 23 |
- | | Week 10:\\ Oct 23 - Oct 27 | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. | [[http:// | + | | Week 10:\\ Oct 26 - Oct 30 | Introduction to Neural Networks |
===== November ===== | ===== November ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Oct 30 - Nov 2 | Classification with Neural Networks | + | | Week 11:\\ Nov 2 - Nov 6 |
- | | Week 12:\\ Nov 5 - Nov 9 | + | | Week 12:\\ Nov 9 - Nov 13 |
- | | Week 13:\\ Nov 12 - Nov 16 | Faster Reinforcement Learning. Autoencoder neural networks. | [[http:// | + | | Week 13:\\ Nov 16 - Nov 20 |
- | | | + | | Nov 23 - Nov 27 | Fall Recess! |
- | | Week 14:\\ Nov 26 - Nov 30 | + | |
===== December ===== | ===== December ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ Dec 3 - Dec 7 | + | | Week 14:\\ Nov 30 - Dec 4 |
- | | Final Exam Week:\\ Dec 10 - Dec 14 | + | | Week 15:\\ Dec 7 - Dec 11 | Recent AI Success |
+ | | Final Exam Week:\\ Dec 14 - Dec 18 | ||
+ | |||