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 | | |
algorithms | shadow a class on algorithms | not started | | |
GRE subject test | learn whatever else is needed | not started | | |
Read Commonsense Reasoning | | not started | | |
Read Knowledge, Representation, and Reasoning | | not started | | |
Read Design Patterns | | barely started | | |
basic algorithms | learn the algs in this http://cstheory.stackexchange.com/questions/19759/core-algorithms-deployed/19773#19773 , mb from CLR | not started | | |
read Java Collections Library | http://www.docjar.com/html/api/java/util/HashMap.java.html | not started | | |
Languages
lisp | scheme, clojure, mb CL, but which others? | not started | read "On Lisp" | |
IO | | not started | | |
self | | not started | | |
ruby | | not started | | |
haskell | | started | | |
scala | | | not started | |
go | | | not started | |
D | | | not started | |
prolog | | not started | | |
forth | | not started | | |
New stuff
Note: the awesome stuff that Vaughn Pratt taught is on mathToLearn, not this page.