coursera-machine-learning
Coursera's Machine Learning by Andrew Ng
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최종 버전 다운로드 (.zip)- computeCost.m
- computeCostMulti.m
- ex1.m
- ex1_multi.m
- ex1data1.txt
- ex1data2.txt
- featureNormalize.m
- gradientDescent.m
- gradientDescentMulti.m
- normalEqn.m
- octave-workspace
- plotData.m
- submit.m
- submitWeb.m
- warmUpExercise.m
- costFunction.m
- costFunctionReg.m
- ex2.m
- ex2_reg.m
- ex2data1.txt
- ex2data2.txt
- mapFeature.m
- octave-workspace
- plotData.m
- plotDecisionBoundary.m
- predict.m
- sigmoid.m
- submit.m
- submitWeb.m
- displayData.m
- ex3.m
- ex3_nn.m
- ex3data1.mat
- ex3weights.mat
- fmincg.m
- lrCostFunction.m
- oneVsAll.m
- predict.m
- predictOneVsAll.m
- sigmoid.m
- submit.m
- submitWeb.m
- checkNNGradients.m
- computeNumericalGradient.m
- debugInitializeWeights.m
- displayData.m
- ex4.m
- ex4data1.mat
- ex4weights.mat
- fmincg.m
- nnCostFunction.m
- predict.m
- randInitializeWeights.m
- sigmoid.m
- sigmoidGradient.m
- submit.m
- submitWeb.m
- ex5.m
- ex5data1.mat
- featureNormalize.m
- fmincg.m
- learningCurve.m
- linearRegCostFunction.m
- plotFit.m
- polyFeatures.m
- submit.m
- submitWeb.m
- trainLinearReg.m
- validationCurve.m
- dataset3Params.m
- emailFeatures.m
- emailSample1.txt
- emailSample2.txt
- ex6.m
- ex6_spam.m
- ex6data1.mat
- ex6data2.mat
- ex6data3.mat
- gaussianKernel.m
- getVocabList.m
- linearKernel.m
- octave-workspace
- 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
- bird_small.mat
- bird_small.png
- computeCentroids.m
- displayData.m
- drawLine.m
- ex7.m
- 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
- submit.m
- submitWeb.m
- checkCostFunction.m
- cofiCostFunc.m
- computeNumericalGradient.m
- estimateGaussian.m
- ex8.m
- 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
- submit.m
- submitWeb.m
- visualizeFit.m
- 1.I. Introduction.pdf
- 1.II. Linear regression with one variable.pdf
- 1.III. Linear Algebra.pdf
- 10. XVII. Large Scale Machine Learning.pdf
- 10. XVIII. Application- Photo OCR.pdf
- 2.IV. Linear Regression with Multiple Variables.pdf
- 2.V. Octave Tutorial.pdf
- 3.VI. Logistic Regression.pdf
- 3.VII. Regularization.pdf
- 4. VIII. Neural Networks- Representation.pdf
- 5. IX. Neural Networks- Learning.pdf
- 6. X. Advice for Applying Machine Learning.pdf
- 6. XI. Machine Learning System Design.pdf
- 7. XII. Support Vector Machines.pdf
- 8. XIII. Clustering.pdf
- 8. XIV. Principal Component Analysis.pdf
- 9. XV. Anomaly Detection.pdf
- 9. XVI. Recommender Systems.pdf
- week1-quiz1.md
- week1-quiz2.md
- week1-quiz3.md
- week2-quiz4.md
- week2-quiz5.md
- week2_quiz4.m
- week2_quiz5.m
- week6_quiz1.m
- .gitignore
- ex1.pdf
- ex2.pdf
- ex3.pdf
- ex4.pdf
- ex5.pdf
- ex6.pdf
- ex7.pdf
- ex8.pdf
- README.md
// repository documentation
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