Index of /~lboloni/Teaching/CAP5636_Fall2020/slides

[ICO]NameLast modifiedSizeDescription
[PARENTDIR]Parent Directory  -  
[ ]01 - History.pdf2021-07-19 11:43 18M 
[ ]02 - Uninformed Search.pptx2021-07-19 11:43 8.2M 
[ ]03 - Informed Search.pptx2021-07-19 11:43 6.0M 
[ ]04 - CSPs 1.pptx2021-07-19 11:43 67M 
[ ]05 - CSPs 2.pptx2021-07-19 11:43 19M 
[ ]06 - Adversarial Search.pptx2021-07-19 11:43 25M 
[ ]07 - Expectimax Search and Utilities.pptx2021-07-19 11:43 22M 
[ ]08 - MDPs 1.pptx2021-07-19 11:43 14M 
[ ]09 - MDPs 2.pptx2021-07-19 11:43 2.8M 
[ ]10 - Reinforcement Learning 1.pptx2021-07-19 11:43 51M 
[ ]11 - Reinforcement Learning 2.pptx2021-07-19 11:44 77M 
[ ]12 - Probability.pptx2021-07-19 11:44 55M 
[ ]13 - Markov Models.pptx2021-07-19 11:44 50M 
[ ]14 - Hidden Markov Models.pptx2021-07-19 11:44 37M 
[ ]15 - Particle Filters and Applications of HMMs.pptx2021-07-19 11:44 84M 
[ ]16 - Bayes Nets 1 - Representation.pptx2021-07-19 11:44 2.3M 
[ ]17 - Bayes Nets 2 - Independence.pptx2021-07-19 11:44 2.4M 
[ ]18 - Bayes Nets 3 - Inference.pptx2021-07-19 11:44 93M 
[ ]19 - Bayes Nets 4 - Sampling.pptx2021-07-19 11:44 2.8M 
[ ]20 - Decision Diagrams and VPI.pptx2021-07-19 11:44 72M 
[ ]21 - Naive Bayes.pptx2021-07-19 11:44 3.3M 
[ ]22 - Deep Learning 1 - Introduction.pptx2021-07-19 11:44 3.0M 
[ ]23 - Deep Learning 2 - Convolutional networks.pptx2021-07-19 11:44 8.2M 
[ ]DL01-Intro.pdf2021-07-19 11:44 1.7M 
[ ]DL02-MLbackground.pptx2021-07-19 11:44 1.2M 
[ ]DL03-Feedforward-NN.pdf2021-07-19 11:44 1.0M 
[ ]DL04-Convolutional-NN.pptx2021-07-19 11:44 6.3M 
[ ]Neural Networks - Activation functions.pptx2021-07-19 11:44 5.5M 
[ ]Neural Networks - Case Studies.pptx2021-07-19 11:44 39M 
[ ]Neural Networks - Convolutional networks.pptx2021-07-19 11:44 6.3M 
[ ]Neural Networks - LSTM.pptx2021-07-19 11:44 9.2M 
[ ]Neural Networks - ML background.pptx2021-07-19 11:44 1.3M 
[ ]Neural Networks - Optimization.pptx2021-07-19 11:44 2.2M 
[ ]desktop.ini2022-02-07 09:37 244  
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