Probabilistic_Reasoning
###UCSD CSE 250A Tasks Principles of Artificial Intelligence: Probabilistic Reasoning and Decision-Making
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Hangman(Java): A Hangman game, giving next best guess and its probability using Bayes deduction for belief networks
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Handwritten_Classification(Python): Recognition of handwritten digits 3 and 5 using logistic regression with Newton's method or gradient ascend
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LWsimulation(Java): Stochastic simulation (likehood weighting) for estimation of a belief network
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Language_Modeling(Python): Statistical language modeling for unigram, bigram and a mixture model
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Stock_Prediction(Python): Prediction of the Nasdaq stock market price
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EM-NoisyOR(Java): Use Expectation Maximum for classification
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Viterbi(Python): Use Viterbi alogorithm for speech recognition, decoding a sentense from observations, given a Hidden Markov Model
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Reinforcement_Learning(Python): Use value iteration and policy iteration in reinforcement learning to slove the maze problem