Material already "learned" in class that should be reviewed (this has first priority because the reward per unit time is better since I already half understand this stuff):
Name | Description | Status | Notes | ||||||
Bayesian networks | Stanford course CS228 | not started | read Jensen's book and reread course notes | ||||||
Read basic AI, ML textbooks | Read Rich & Knight, Mitchell, Langley, Manning, Nilsson, Duda et al, Russel & Norvig books cover to cover | in the middle of Rich & Knight | been dying to read these for years... | ||||||
Read neural net textbooks | Read Bishop, Haykin | in the middle of Bishop, on hold | |||||||
Review quantum computation course notes | Stanford used to offer a course by Colin Williams -- it was great | not started | Maybe should get one of Colin's books 1 2 | ||||||
Review course reader from CS227 | "Artificial Intelligence Algorithms" | not started |
New stuff:
Name | Description | Status | Notes | ||||||
databases and database theory | not started | ||||||||
programming language theory | not started | ||||||||
parallel programming/computation | read a few overviews of types of parallel computing architectures | ||||||||
stochastic programming | not started |
Note: the awesome stuff that Vaughn Pratt taught is on mathToLearn, not this page.