notes

• intro class
• Thu Sep 3 - discuss (schedule & book chapters), (AI background), vacuum world
• Tue Sep 8 - agents, vacuum world, and search ; chap 2 & 3.
• Thu Sep 10 - search 101
• Tue Sep 15 - more search, chap 3,4,5 : genetic algorithm & nqueens
• Thu Sep 17 - finish search. Start logic ?
• Tue Sep 22 - propositional logic, conjuctive normal form, resolution search, wumpus world
• Thu Sep 24 - finish propositional logic; start first order logic
• Tue Sep 29 - inference in first order logic
• Thu Oct 1 - same
• Tue Oct 6 - finish first order logic
• Thu Oct 8 - class presentations on related applications
• Tue Oct 13 - start probabilistic approaches
• Thu Oct 15 - continue Bayesian probability ; start spam filtering
• Tue Oct 20 - Hendrick's Days - no class
• Thu Oct 22 - project check-in
• Tue Oct 27 - projects due ; continue Bayesian networks
• Thu Oct 29 - show'n'tell projects ; Gibbs sampling (finish chap 14)
• Tue Nov 3 - go over Gibbs homework ; start chap 15 (add time)
• Thu Nov 5 - hidden markov models ; forward algorithm
• Tue Nov 10 - the dow jones HMM problem - liklihood of observables
• Thu Nov 12 - HMM : forward, Viterbi, particle filter algorithms
• Tue Nov 17 - discuss final projects ; start neural nets
• Thu Nov 19 - chap1 of neuralnetworksanddeeplearning
• Tue Nov 24 - continue neural net discussion
• Tue Dec 1 - deep neural nets
• Thu Dec 3 - other topics