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====== Schedule ====== | ====== Schedule ====== | ||
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+ | ===== Announcements ===== | ||
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+ | Lecture and office hour videos are available from the Home page of our | ||
+ | [[https:// | ||
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+ | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | ||
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+ | export PATH=/ | ||
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+ | 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 1:\\ Aug 24 - Aug 28 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. | ||
+ | |||
+ | ===== September ===== | ||
+ | |||
+ | |< 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 7:\\ Oct 5 - Oct 9 | Reinforcement Learning for Two-Player Games. | ||
+ | | Week 8:\\ Oct 12 - Oct 16 | Introduction to Neural Networks | ||
+ | | Week 9:\\ Oct 19 - Oct 23 | More Neural Networks. Autoencoders. | ||
+ | | Week 10:\\ Oct 26 - Oct 30 | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. | ||
+ | |||
+ | ===== November ===== | ||
+ | |||
+ | |< 100% 18% 20% 22% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 11:\\ Nov 2 - Nov 6 | Classification with Neural Networks. Reinforcement Learning with Neural Networks. | ||
+ | | Week 12:\\ Nov 9 - Nov 13 | Introduction to Pytorch.\\ Constraint satisfaction.\\ Min-conflicts. | ||
+ | | Week 13:\\ Nov 16 - Nov 20 | Natural language understanding and translation. | ||
+ | | Nov 23 - Nov 27 | Fall Recess! | ||
+ | |||
+ | ===== December ===== | ||
+ | |||
+ | |< 100% 18% 20% 22% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | 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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