Download Machine Learning [Stanford University Online Course] [2011, ENG] Torrent

Torrent Contents Size: 1.78 GB

Machine Learning [Stanford University Online Course] [2011, ENG]

Lecture Slides

Lecture1.pdf	PDF	4.71 MB
Lecture1.pptx	PPTX	4.54 MB
Lecture10.pdf	PDF	1.48 MB
Lecture10.pptx	PPTX	3.35 MB
Lecture11.pdf	PDF	1.16 MB
Lecture11.pptx	PPTX	7.17 MB
Lecture12.pdf	PDF	2.3 MB
Lecture12.pptx	PPTX	5.39 MB
Lecture13.pdf	PDF	2.17 MB
Lecture13.pptx	PPTX	2.79 MB
Lecture14.pdf	PDF	1.61 MB
Lecture14.pptx	PPTX	3.62 MB
Lecture15.pdf	PDF	3.33 MB
Lecture15.pptx	PPTX	6.05 MB
Lecture16.pdf	PDF	1.42 MB
Lecture16.pptx	PPTX	3.6 MB
Lecture17.pdf	PDF	1.98 MB
Lecture17.pptx	PPTX	3.78 MB
Lecture18.pdf	PDF	1.97 MB
Lecture18.pptx	PPTX	6.13 MB
Lecture2.pdf	PDF	2.88 MB
Lecture2.pptx	PPTX	5.35 MB
Lecture3.pdf	PDF	1.8 MB
Lecture3.pptx	PPTX	4.92 MB
Lecture4.pdf	PDF	1.7 MB
Lecture4.pptx	PPTX	4.4 MB
Lecture6.pdf	PDF	1.8 MB
Lecture6.pptx	PPTX	3.24 MB
Lecture7.pdf	PDF	1.4 MB
Lecture7.pptx	PPTX	2.58 MB
Lecture8.pdf	PDF	5.23 MB
Lecture8.pptx	PPTX	6.29 MB
Lecture9.pdf	PDF	3.37 MB
Lecture9.pptx	PPTX	4.96 MB
octave_session.m	M	5.21 KB

MSBNx.exe

EXE

10.9 MB

Octave-3.2.4_i686-pc-mingw32_gcc-4.4.0_setup.exe

EXE

69.61 MB

Octave.Workshop.Installer.exe

EXE

117.11 MB

Programming Exercises

mlclass-ex1.zip	ZIP	462.67 KB
mlclass-ex2.zip	ZIP	239.96 KB
mlclass-ex3.zip	ZIP	7.54 MB
mlclass-ex4.zip	ZIP	7.59 MB
mlclass-ex5.zip	ZIP	126.29 KB
mlclass-ex6.zip	ZIP	894.24 KB
mlclass-ex7.zip	ZIP	11.05 MB
mlclass-ex8.zip	ZIP	792.41 KB

Programming Exercises (completed)

mlclass-ex1.rar	RAR	10.98 KB
mlclass-ex2.rar	RAR	15.25 KB
mlclass-ex3.rar	RAR	7.25 MB
mlclass-ex4.rar	RAR	7.26 MB
mlclass-ex5.rar	RAR	16.36 KB
mlclass-ex6.rar	RAR	568.51 KB
mlclass-ex7.rar	RAR	10.28 MB
mlclass-ex8.rar	RAR	546.91 KB

Review Questions

01 - Introduction.mht	MHT	284.72 KB
02 - Linear regression with one variable.mht	MHT	307.72 KB
03 - Linear Algebra.mht	MHT	309.98 KB
04 - Linear Regression with Multiple Variables.mht	MHT	302.38 KB
05 - Octave Tutorial.mht	MHT	293.41 KB
06 - Logistic Regression.mht	MHT	349.34 KB
07 - Regularization.mht	MHT	351.71 KB
08 - Neural Networks - Representation.mht	MHT	468.13 KB
09 - Neural Networks - Learning.mht	MHT	304.06 KB
10 - Advice for Applying Machine Learning.mht	MHT	321.71 KB
11 - Machine Learning System Design.mht	MHT	296.39 KB
12 - Support Vector Machines.mht	MHT	659.61 KB
13 - Clustering.mht	MHT	298.4 KB
14 - Dimensionality Reduction.mht	MHT	438.82 KB
15 - Anomaly Detection.mht	MHT	353.33 KB
16 - Recommender Systems.mht	MHT	316.59 KB
17 - Large Scale Machine Learning.mht	MHT	300.21 KB
18 - Application Example - Photo OCR.mht	MHT	451.07 KB

Video Lectures

01.1-V3-Introduction-Welcome.mp4	MP4	16.05 MB
01.2-V2-Introduction-WhatIsMachineLearning.mp4	MP4	11.44 MB
01.3-V2-Introduction-SupervisedLearning.mp4	MP4	13.65 MB
01.4-V2-Introduction-UnsupervisedLearning.mp4	MP4	18.17 MB
02.1-V2-LinearRegressionWithOneVariable-ModelRepresentation.mp4	MP4	9.49 MB
02.2-V2-LinearRegressionWithOneVariable-CostFunction.mp4	MP4	9.63 MB
02.3-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionI.mp4	MP4	12.91 MB
02.4-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionII.mp4	MP4	13.92 MB
02.5-V2-LinearRegressionWithOneVariable-GradientDescent.mp4	MP4	14.93 MB
02.6-V2-LinearRegressionWithOneVariable-GradientDescentIntuition.mp4	MP4	13.91 MB
02.7-V2-LinearRegressionWithOneVariable-GradientDescentForLinearRegression.mp4	MP4	13.55 MB
02.8-V2-What'sNext.mp4	MP4	6.09 MB
03.1-V2-LinearAlgebraReview(Optional)-MatricesAndVectors.mp4	MP4	9.79 MB
03.2-V2-LinearAlgebraReview(Optional)-AdditionAndScalarMultiplication.mp4	MP4	7.85 MB
03.3-V2-LinearAlgebraReview(Optional)-MatrixVectorMultiplication.mp4	MP4	15.9 MB
03.4-V2-LinearAlgebraReview(Optional)-MatrixMatrixMultiplication.mp4	MP4	13.81 MB
03.5-V2-LinearAlgebraReview(Optional)-MatrixMultiplicationProperties.mp4	MP4	10.16 MB
03.6-V2-LinearAlgebraReview(Optional)-InverseAndTranspose.mp4	MP4	14.13 MB
04.1-LinearRegressionWithMultipleVariables-MultipleFeatures.mp4	MP4	6.13 MB
04.2-LinearRegressionWithMultipleVariables-GradientDescentForMultipleVariables.mp4	MP4	4.74 MB
04.3-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIFeatureScaling.mp4	MP4	7.58 MB
04.4-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIILearningRate.mp4	MP4	6.86 MB
04.5-LinearRegressionWithMultipleVariables-FeaturesAndPolynomialRegression.mp4	MP4	5.74 MB
04.6-V2-LinearRegressionWithMultipleVariables-NormalEquation.mp4	MP4	13.34 MB
04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional).mp4	MP4	5.18 MB
05.1-OctaveTutorial-BasicOperations.mp4	MP4	20.69 MB
05.2-OctaveTutorial-MovingDataAround.mp4	MP4	25.42 MB
05.3-OctaveTutorial-ComputingOnData.mp4	MP4	10.37 MB
05.4-OctaveTutorial-PlottingData.mp4	MP4	11.31 MB
05.5-OctaveTutorial-ForWhileIfStatementsAndFunctions.mp4	MP4	19.69 MB
05.6-OctaveTutorial-Vectorization.mp4	MP4	16.83 MB
05.7-OctaveTutorial-WorkingOnAndSubmittingProgrammingExercises.mp4	MP4	7.25 MB
06.1-LogisticRegression-Classification.mp4	MP4	8.73 MB
06.2-LogisticRegression-HypothesisRepresentation.mp4	MP4	8.81 MB
06.3-LogisticRegression-DecisionBoundary.mp4	MP4	17.51 MB
06.4-LogisticRegression-CostFunction.mp4	MP4	14.11 MB
06.5-LogisticRegression-SimplifiedCostFunctionAndGradientDescent.mp4	MP4	13.07 MB
06.6-LogisticRegression-AdvancedOptimization.mp4	MP4	21.59 MB
06.7-LogisticRegression-MultiClassClassificationOneVsAll.mp4	MP4	7.29 MB
07.1-Regularization-TheProblemOfOverfitting.mp4	MP4	11.96 MB
07.2-Regularization-CostFunction.mp4	MP4	12.43 MB
07.3-Regularization-RegularizedLinearRegression.mp4	MP4	12.77 MB
07.4-Regularization-RegularizedLogisticRegression.mp4	MP4	13.5 MB
08.1-NeuralNetworksRepresentation-NonLinearHypotheses.mp4	MP4	11.53 MB
08.2-NeuralNetworksRepresentation-NeuronsAndTheBrain.mp4	MP4	11.47 MB
08.3-NeuralNetworksRepresentation-ModelRepresentationI.mp4	MP4	14.37 MB
08.4-NeuralNetworksRepresentation-ModelRepresentationII.mp4	MP4	14.41 MB
08.5-NeuralNetworksRepresentation-ExamplesAndIntuitionsI.mp4	MP4	8.29 MB
08.6-NeuralNetworksRepresentation-ExamplesAndIntuitionsII.mp4	MP4	16.84 MB
08.7-NeuralNetworksRepresentation-MultiClassClassification.mp4	MP4	5.41 MB
09.1-NeuralNetworksLearning-CostFunction.mp4	MP4	8.1 MB
09.2-NeuralNetworksLearning-BackpropagationAlgorithm.mp4	MP4	15.07 MB
09.3-NeuralNetworksLearning-BackpropagationIntuition.mp4	MP4	17.14 MB
09.3-NeuralNetworksLearning-ImplementationNoteUnrollingParameters.mp4	MP4	10.54 MB
09.4-NeuralNetworksLearning-GradientChecking.mp4	MP4	14.76 MB
09.5-NeuralNetworksLearning-RandomInitialization.mp4	MP4	7.95 MB
09.7-NeuralNetworksLearning-PuttingItTogether.mp4	MP4	17.88 MB
09.8-NeuralNetworksLearning-AutonomousDrivingExample.mp4	MP4	21.25 MB
10.1-AdviceForApplyingMachineLearning-DecidingWhatToTryNext.mp4	MP4	7.58 MB
10.2-AdviceForApplyingMachineLearning-EvaluatingAHypothesis.mp4	MP4	9.52 MB
10.3-AdviceForApplyingMachineLearning-ModelSelectionAndTrainValidationTestSets.mp4	MP4	16.13 MB
10.4-AdviceForApplyingMachineLearning-DiagnosingBiasVsVariance.mp4	MP4	10.42 MB
10.5-AdviceForApplyingMachineLearning-RegularizationAndBiasVariance.mp4	MP4	13.87 MB
10.6-AdviceForApplyingMachineLearning-LearningCurves.mp4	MP4	13.54 MB
10.7-AdviceForApplyingMachineLearning-DecidingWhatToDoNextRevisited.mp4	MP4	8.94 MB
11.1-MachineLearningSystemDesign-PrioritizingWhatToWorkOn.mp4	MP4	12.32 MB
11.2-MachineLearningSystemDesign-ErrorAnalysis.mp4	MP4	16.94 MB
11.3-MachineLearningSystemDesign-ErrorMetricsForSkewedClasses.mp4	MP4	14.24 MB
11.4-MachineLearningSystemDesign-TradingOffPrecisionAndRecall.mp4	MP4	17.29 MB
11.5-MachineLearningSystemDesign-DataForMachineLearning.mp4	MP4	13.98 MB
12.1-SupportVectorMachines-OptimizationObjective.mp4	MP4	17.77 MB
12.2-SupportVectorMachines-LargeMarginIntuition.mp4	MP4	12.66 MB
12.3-SupportVectorMachines-MathematicsBehindLargeMarginClassificationOptional.mp4	MP4	22.91 MB
12.4-SupportVectorMachines-KernelsI.mp4	MP4	18.74 MB
12.5-SupportVectorMachines-KernelsII.mp4	MP4	18.31 MB
12.6-SupportVectorMachines-UsingAnSVM.mp4	MP4	25.76 MB
14.1-Clustering-UnsupervisedLearningIntroduction.mp4	MP4	4.12 MB
14.2-Clustering-KMeansAlgorithm.mp4	MP4	15.36 MB
14.3-Clustering-OptimizationObjective.mp4	MP4	8.78 MB
14.4-Clustering-RandomInitialization.mp4	MP4	9.31 MB
14.5-Clustering-ChoosingTheNumberOfClusters.mp4	MP4	10.11 MB
15.1-DimensionalityReduction-MotivationIDataCompression.mp4	MP4	17.63 MB
15.2-DimensionalityReduction-MotivationIIVisualization.mp4	MP4	6.91 MB
15.3-DimensionalityReduction-PrincipalComponentAnalysisProblemFormulation.mp4	MP4	11.4 MB
15.4-DimensionalityReduction-PrincipalComponentAnalysisAlgorithm.mp4	MP4	19.4 MB
15.5-DimensionalityReduction-ChoosingTheNumberOfPrincipalComponents.mp4	MP4	12.47 MB
15.6-DimensionalityReduction-ReconstructionFromCompressedRepresentation.mp4	MP4	5.93 MB
15.7-DimensionalityReduction-AdviceForApplyingPCA.mp4	MP4	15.8 MB
16.1-AnomalyDetection-ProblemMotivation-V1.mp4	MP4	8.83 MB
16.2-AnomalyDetection-GaussianDistribution.mp4	MP4	12.88 MB
16.3-AnomalyDetection-Algorithm.mp4	MP4	15.3 MB
16.4-AnomalyDetection-DevelopingAndEvaluatingAnAnomalyDetectionSystem.mp4	MP4	16.92 MB
16.5-AnomalyDetection-AnomalyDetectionVsSupervisedLearning-V1.mp4	MP4	10.79 MB
16.7-AnomalyDetection-MultivariateGaussianDistribution-OPTIONAL.mp4	MP4	17.27 MB
16.8-AnomalyDetection-AnomalyDetectionUsingTheMultivariateGaussianDistribution-OPTIONAL.mp4	MP4	17.75 MB
17.1-RecommenderSystems-ProblemFormulation.mp4	MP4	13.65 MB
17.2-RecommenderSystems-ContentBasedRecommendations.mp4	MP4	18.73 MB
17.3-RecommenderSystems-CollaborativeFiltering-V1.mp4	MP4	13.1 MB
17.4-RecommenderSystems-CollaborativeFilteringAlgorithm.mp4	MP4	11.44 MB
17.6-RecommenderSystems-ImplementationalDetailMeanNormalization.mp4	MP4	10.46 MB
18.1-LargeScaleMachineLearning-LearningWithLargeDatasets.mp4	MP4	7.12 MB
18.2-LargeScaleMachineLearning-StochasticGradientDescent.mp4	MP4	16.4 MB
18.3-LargeScaleMachineLearning-MiniBatchGradientDescent.mp4	MP4	7.99 MB
18.4-LargeScaleMachineLearning-StochasticGradientDescentConvergence.mp4	MP4	14.41 MB
18.5-LargeScaleMachineLearning-OnlineLearning.mp4	MP4	15.96 MB
18.6-LargeScaleMachineLearning-MapReduceAndDataParallelism.mp4	MP4	17.3 MB
19.1-ApplicationExamplePhotoOCR-ProblemDescriptionAndPipeline.mp4	MP4	8.54 MB
19.2-ApplicationExamplePhotoOCR-SlidingWindows.mp4	MP4	18.04 MB
19.3-ApplicationExamplePhotoOCR-GettingLotsOfDataArtificialDataSynthesis.mp4	MP4	20.4 MB
19.4-ApplicationExamplePhotoOCR-CeilingAnalysisWhatPartOfThePipelineToWorkOnNext.mp4	MP4	17.83 MB
20.1-Conclusion-SummaryAndThankYou.mp4	MP4	4.52 MB

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Machine Learning [Stanford University Online Course] [2011, ENG]

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