├── .project ├── .pydevproject ├── AI ├── BayesNetworks │ ├── __init__.py │ ├── bayes_net.py │ ├── examples.py │ └── homework_2.py ├── ComputerVision │ ├── __init__.py │ ├── examples.py │ └── filters.py ├── Exams │ ├── __init__.py │ ├── final.py │ ├── homework_6.py │ └── midterm.py ├── Game │ ├── __init__.py │ ├── example.py │ └── game.py ├── Logic │ ├── __init__.py │ ├── examples.py │ ├── homework_4.py │ └── logic.py ├── MDP │ ├── __init__.py │ ├── example_1.py │ ├── example_2.py │ └── grid.py ├── MachineLearning │ ├── __init__.py │ ├── bayes.py │ ├── examples.py │ ├── homework.py │ └── linear_regression.py ├── Markov │ ├── __init__.py │ ├── examples.py │ └── markov.py ├── ProblemSolving │ ├── __init__.py │ ├── examples.py │ ├── homework_1.py │ └── search.py └── Robotic │ ├── __init__.py │ ├── homework.py │ └── motion.py ├── ComputationalInvesting ├── data │ └── orders.csv ├── hw1.py ├── hw2.py ├── hw3.py ├── hw4.py └── qenv.py ├── ML ├── ex1 │ ├── computeCost.m │ ├── ex1.m │ ├── ex1.pdf │ ├── ex1_multi.m │ ├── ex1data1.txt │ ├── ex1data2.txt │ ├── featureNormalize.m │ ├── gradientDescent.m │ └── normalEqn.m ├── ex2 │ ├── costFunction.m │ ├── costFunctionReg.m │ ├── ex2.m │ ├── ex2.pdf │ ├── ex2_reg.m │ ├── ex2data1.txt │ ├── ex2data2.txt │ ├── mapFeature.m │ ├── plotData.m │ ├── plotDecisionBoundary.m │ ├── predict.m │ └── sigmoid.m ├── ex3 │ ├── displayData.m │ ├── ex3.m │ ├── ex3.pdf │ ├── ex3_nn.m │ ├── ex3data1.mat │ ├── ex3weights.mat │ ├── fmincg.m │ ├── lrCostFunction.m │ ├── oneVsAll.m │ ├── predict.m │ ├── predictOneVsAll.m │ └── sigmoid.m ├── ex4 │ ├── checkNNGradients.m │ ├── computeNumericalGradient.m │ ├── debugInitializeWeights.m │ ├── displayData.m │ ├── ex4.m │ ├── ex4.pdf │ ├── ex4data1.mat │ ├── ex4weights.mat │ ├── fmincg.m │ ├── nnCostFunction.m │ ├── predict.m │ ├── randInitializeWeights.m │ ├── sigmoid.m │ └── sigmoidGradient.m ├── ex5 │ ├── ex5.m │ ├── ex5.pdf │ ├── ex5data1.mat │ ├── featureNormalize.m │ ├── fmincg.m │ ├── learningCurve.m │ ├── linearRegCostFunction.m │ ├── plotFit.m │ ├── polyFeatures.m │ ├── trainLinearReg.m │ └── validationCurve.m ├── ex6 │ ├── dataset3Params.m │ ├── emailFeatures.m │ ├── emailSample1.txt │ ├── emailSample2.txt │ ├── ex6.m │ ├── ex6.pdf │ ├── ex6_spam.m │ ├── ex6data1.mat │ ├── ex6data2.mat │ ├── ex6data3.mat │ ├── gaussianKernel.m │ ├── getVocabList.m │ ├── linearKernel.m │ ├── plotData.m │ ├── porterStemmer.m │ ├── processEmail.m │ ├── readFile.m │ ├── spamSample1.txt │ ├── spamSample2.txt │ ├── spamTest.mat │ ├── spamTrain.mat │ ├── submit.m │ ├── submitWeb.m │ ├── svmPredict.m │ ├── svmTrain.m │ ├── visualizeBoundary.m │ ├── visualizeBoundaryLinear.m │ └── vocab.txt ├── ex7 │ ├── bird_small.png │ ├── computeCentroids.m │ ├── displayData.m │ ├── drawLine.m │ ├── ex7.m │ ├── ex7.pdf │ ├── ex7_pca.m │ ├── ex7data1.mat │ ├── ex7data2.mat │ ├── ex7faces.mat │ ├── featureNormalize.m │ ├── findClosestCentroids.m │ ├── kMeansInitCentroids.m │ ├── pca.m │ ├── plotDataPoints.m │ ├── plotProgresskMeans.m │ ├── projectData.m │ ├── recoverData.m │ └── runkMeans.m └── ex8 │ ├── checkCostFunction.m │ ├── cofiCostFunc.m │ ├── computeNumericalGradient.m │ ├── estimateGaussian.m │ ├── ex8.m │ ├── ex8.pdf │ ├── ex8_cofi.m │ ├── ex8_movieParams.mat │ ├── ex8_movies.mat │ ├── ex8data1.mat │ ├── ex8data2.mat │ ├── fmincg.m │ ├── loadMovieList.m │ ├── movie_ids.txt │ ├── multivariateGaussian.m │ ├── normalizeRatings.m │ ├── selectThreshold.m │ └── visualizeFit.m ├── NLP ├── HMM_Tagger │ ├── count_freqs.py │ ├── eval_gene_tagger.py │ ├── gene.dev │ ├── gene.key │ ├── gene.train │ └── gene_tagger.py └── PCFG_CKY │ ├── eval_parser.py │ ├── parse_dev.dat │ ├── parse_dev.key │ ├── parse_train.dat │ ├── parse_train_vert.dat │ └── pcfg.py ├── README └── Robotics ├── exam ├── gaussian.py ├── localization.py └── warehouse_robot.py ├── histogram ├── homework.py └── unit_1.py ├── kalman ├── gauss.py ├── homework.py ├── matrix.py └── unit_2.py ├── particle ├── 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