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====== Schedule ====== | ====== Schedule ====== | ||
+ | |||
+ | ===== Announcements ===== | ||
+ | |||
+ | Sept 7: Assignment 2 is now complete. | ||
+ | |||
+ | Aug 31: Assignment 1 now includes another example. | ||
+ | |||
+ | |||
+ | Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https:// | ||
+ | |||
+ | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | ||
+ | |||
+ | export PATH=/ | ||
+ | |||
+ | /* | ||
+ | are available at this [[https:// | ||
+ | */ | ||
+ | |||
+ | |||
+ | ===== August ===== | ||
+ | |||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 1:\\ Aug 21 - Aug 25 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. | ||
+ | | Week 2:\\ Aug 28 - Sept 1 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. | ||
+ | |||
+ | |||
+ | ===== September ===== | ||
+ | |||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 3:\\ Sept 4 - Sept 8 | Informed search. A* search. Python classes, sorting, numpy arrays. | ||
+ | | Week 4:\\ Sept 11 - Sept 15 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | ||
+ | | Week 5:\\ Sept 18 - Sept 22 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | ||
+ | | Week 6:\\ Sept 25 - Sept 29 | Negamax, with pruning. | [[http:// | ||
+ | |||
+ | ===== October ===== | ||
+ | |||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 7:\\ Oct 2 - Oct 6 | Introduction to Reinforcement Learning. | ||
+ | | Week 8:\\ Oct 9 - Oct 13 | Reinforcement Learning for Two-Player Games.\\ Introduction to Neural Networks | ||
+ | | Week 9:\\ Oct 16 - Oct 20 | More Neural Networks | ||
+ | | Week 10:\\ Oct 23 - Oct 27 | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. | ||
+ | |||
+ | ===== November ===== | ||
+ | |||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 11:\\ Oct 30 - Nov 3 | Classification with Neural Networks | ||
+ | | Week 12:\\ Nov 6 - Nov 10 | Reinforcement Learning with Neural Networks.\\ Lecture and Chuck' | ||
+ | | Week 13:\\ Nov 13 - Nov 17 | Faster Reinforcement Learning. Autoencoder neural networks. | ||
+ | | Nov 20 - Nov 24 | Fall Break | | ||
+ | | Week 14:\\ Nov 27 - Dec 1 | Constraint satisfaction. Min-conflicts | ||
+ | |||
+ | ===== December ===== | ||
+ | |||
+ | |< 100% 10% 20% 30% 20% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 15:\\ Dec 4 - Dec 8 | Recurrent neural networks and use in natural language\\ <color red>Dec 7, Thursday, PLEASE ATTEND. Course Surveys will be filled out.</ | ||
+ | | Finals Week:\\ Dec 11 - Dec 15 | | ||