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种子哈希:
1318bae60185f4e0e013e1667230f3930a4573b9
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1.58G
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极快
收录时间:
2017-09-11
最近下载:
2021-03-25
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文件列表
01.1-V3-Introduction-Welcome.mp4
14.9 MB
01.2-V2-Introduction-WhatIsMachineLearning.mp4
31.9 MB
01.3-V2-Introduction-SupervisedLearning.mp4
16.2 MB
01.4-V2-Introduction-UnsupervisedLearning.mp4
40.4 MB
02.1-V2-LinearRegressionWithOneVariable-ModelRepresentation.mp4
12.2 MB
02.2-V2-LinearRegressionWithOneVariable-CostFunction.mp4
13.7 MB
02.3-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionI.mp4
17.1 MB
02.4-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionII.mp4
33.2 MB
02.5-V2-LinearRegressionWithOneVariable-GradientDescent.mp4
28.3 MB
02.6-V2-LinearRegressionWithOneVariable-GradientDescentIntuition.mp4
19.8 MB
02.7-V2-LinearRegressionWithOneVariable-GradientDescentForLinearRegression.mp4
26.7 MB
02.8-V2-What'sNext.mp4
7.7 MB
03.1-V2-LinearAlgebraReview(Optional)-MatricesAndVectors.mp4
12.5 MB
03.2-V2-LinearAlgebraReview(Optional)-AdditionAndScalarMultiplication.mp4
9.7 MB
03.3-V2-LinearAlgebraReview(Optional)-MatrixVectorMultiplication.mp4
21.2 MB
03.4-V2-LinearAlgebraReview(Optional)-MatrixMatrixMultiplication.mp4
23.4 MB
03.5-V2-LinearAlgebraReview(Optional)-MatrixMultiplicationProperties.mp4
12.3 MB
03.6-V2-LinearAlgebraReview(Optional)-InverseAndTranspose.mp4
25.8 MB
04.1-LinearRegressionWithMultipleVariables-MultipleFeatures.mp4
6.4 MB
04.2-LinearRegressionWithMultipleVariables-GradientDescentForMultipleVariables.mp4
5.0 MB
04.3-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIFeatureScaling.mp4
8.0 MB
04.4-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIILearningRate.mp4
7.2 MB
04.5-LinearRegressionWithMultipleVariables-FeaturesAndPolynomialRegression.mp4
6.0 MB
04.6-V2-LinearRegressionWithMultipleVariables-NormalEquation.mp4
14.0 MB
04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional).mp4
5.4 MB
05.1-OctaveTutorial-BasicOperations.mp4
21.7 MB
05.2-OctaveTutorial-MovingDataAround.mp4
26.7 MB
05.3-OctaveTutorial-ComputingOnData.mp4
10.9 MB
05.4-OctaveTutorial-PlottingData.mp4
11.9 MB
05.5-OctaveTutorial-ForWhileIfStatementsAndFunctions.mp4
20.6 MB
05.6-OctaveTutorial-Vectorization.mp4
17.6 MB
05.7-OctaveTutorial-WorkingOnAndSubmittingProgrammingExercises.mp4
7.6 MB
06.1-LogisticRegression-Classification.mp4
9.2 MB
06.2-LogisticRegression-HypothesisRepresentation.mp4
9.2 MB
06.3-LogisticRegression-DecisionBoundary.mp4
18.4 MB
06.4-LogisticRegression-CostFunction.mp4
14.8 MB
06.5-LogisticRegression-SimplifiedCostFunctionAndGradientDescent.mp4
13.7 MB
06.6-LogisticRegression-AdvancedOptimization.mp4
22.6 MB
06.7-LogisticRegression-MultiClassClassificationOneVsAll.mp4
7.6 MB
07.1-Regularization-TheProblemOfOverfitting.mp4
12.5 MB
07.2-Regularization-CostFunction.mp4
13.0 MB
07.3-Regularization-RegularizedLinearRegression.mp4
13.4 MB
07.4-Regularization-RegularizedLogisticRegression.mp4
14.2 MB
08.1-NeuralNetworksRepresentation-NonLinearHypotheses.mp4
12.1 MB
08.2-NeuralNetworksRepresentation-NeuronsAndTheBrain.mp4
12.0 MB
08.3-NeuralNetworksRepresentation-ModelRepresentationI.mp4
15.1 MB
08.4-NeuralNetworksRepresentation-ModelRepresentationII.mp4
15.1 MB
08.5-NeuralNetworksRepresentation-ExamplesAndIntuitionsI.mp4
8.7 MB
08.6-NeuralNetworksRepresentation-ExamplesAndIntuitionsII.mp4
17.7 MB
08.7-NeuralNetworksRepresentation-MultiClassClassification.mp4
5.7 MB
09.1-NeuralNetworksLearning-CostFunction.mp4
8.5 MB
09.2-NeuralNetworksLearning-BackpropagationAlgorithm.mp4
15.8 MB
09.3-NeuralNetworksLearning-BackpropagationIntuition.mp4
18.0 MB
09.4-NeuralNetworksLearning-ImplementationNoteUnrollingParameters.mp4
11.1 MB
09.5-NeuralNetworksLearning-GradientChecking.mp4
15.5 MB
09.6-NeuralNetworksLearning-RandomInitialization.mp4
8.3 MB
09.7-NeuralNetworksLearning-PuttingItTogether.mp4
18.7 MB
09.8-NeuralNetworksLearning-AutonomousDrivingExample.mp4
22.3 MB
10.1-AdviceForApplyingMachineLearning-DecidingWhatToTryNext.mp4
8.0 MB
10.2-AdviceForApplyingMachineLearning-EvaluatingAHypothesis.mp4
10.0 MB
10.3-AdviceForApplyingMachineLearning-ModelSelectionAndTrainValidationTestSets.mp4
16.9 MB
10.4-AdviceForApplyingMachineLearning-DiagnosingBiasVsVariance.mp4
10.9 MB
10.5-AdviceForApplyingMachineLearning-RegularizationAndBiasVariance.mp4
14.5 MB
10.6-AdviceForApplyingMachineLearning-LearningCurves.mp4
14.2 MB
10.7-AdviceForApplyingMachineLearning-DecidingWhatToDoNextRevisited.mp4
9.4 MB
11.1-MachineLearningSystemDesign-PrioritizingWhatToWorkOn.mp4
12.9 MB
11.2-MachineLearningSystemDesign-ErrorAnalysis.mp4
17.8 MB
11.3-MachineLearningSystemDesign-ErrorMetricsForSkewedClasses.mp4
14.9 MB
11.4-MachineLearningSystemDesign-TradingOffPrecisionAndRecall.mp4
18.1 MB
11.5-MachineLearningSystemDesign-DataForMachineLearning.mp4
14.7 MB
12.1-SupportVectorMachines-OptimizationObjective.mp4
18.6 MB
12.2-SupportVectorMachines-LargeMarginIntuition.mp4
13.3 MB
12.3-SupportVectorMachines-MathematicsBehindLargeMarginClassificationOptional.mp4
24.0 MB
12.4-SupportVectorMachines-KernelsI.mp4
19.7 MB
12.5-SupportVectorMachines-KernelsII.mp4
19.2 MB
12.6-SupportVectorMachines-UsingAnSVM.mp4
27.0 MB
14.1-Clustering-UnsupervisedLearningIntroduction.mp4
4.3 MB
14.2-Clustering-KMeansAlgorithm.mp4
16.1 MB
14.3-Clustering-OptimizationObjective.mp4
9.2 MB
14.4-Clustering-RandomInitialization.mp4
9.8 MB
14.5-Clustering-ChoosingTheNumberOfClusters.mp4
10.6 MB
15.1-DimensionalityReduction-MotivationIDataCompression.mp4
18.5 MB
15.2-DimensionalityReduction-MotivationIIVisualization.mp4
7.2 MB
15.3-DimensionalityReduction-PrincipalComponentAnalysisProblemFormulation.mp4
12.0 MB
15.4-DimensionalityReduction-PrincipalComponentAnalysisAlgorithm.mp4
20.3 MB
15.5-DimensionalityReduction-ChoosingTheNumberOfPrincipalComponents.mp4
13.1 MB
15.6-DimensionalityReduction-ReconstructionFromCompressedRepresentation.mp4
6.2 MB
15.7-DimensionalityReduction-AdviceForApplyingPCA.mp4
16.6 MB
16.1-AnomalyDetection-ProblemMotivation-V1.mp4
9.3 MB
16.2-AnomalyDetection-GaussianDistribution.mp4
13.5 MB
16.3-AnomalyDetection-Algorithm.mp4
16.0 MB
16.4-AnomalyDetection-DevelopingAndEvaluatingAnAnomalyDetectionSystem.mp4
17.7 MB
16.5-AnomalyDetection-AnomalyDetectionVsSupervisedLearning-V1.mp4
11.3 MB
16.6-AnomalyDetection-ChoosingWhatFeaturesToUse.mp4
16.2 MB
16.7-AnomalyDetection-MultivariateGaussianDistribution-OPTIONAL.mp4
18.1 MB
16.8-AnomalyDetection-AnomalyDetectionUsingTheMultivariateGaussianDistribution-OPTIONAL.mp4
18.6 MB
17.1-RecommenderSystems-ProblemFormulation.mp4
14.3 MB
17.2-RecommenderSystems-ContentBasedRecommendations.mp4
19.6 MB
17.3-RecommenderSystems-CollaborativeFiltering-V1.mp4
13.7 MB
17.4-RecommenderSystems-CollaborativeFilteringAlgorithm.mp4
12.0 MB
17.5-RecommenderSystems-VectorizationLowRankMatrixFactorization.mp4
11.0 MB
17.6-RecommenderSystems-ImplementationalDetailMeanNormalization.mp4
11.0 MB
18.1-LargeScaleMachineLearning-LearningWithLargeDatasets.mp4
7.5 MB
18.2-LargeScaleMachineLearning-StochasticGradientDescent.mp4
17.2 MB
18.3-LargeScaleMachineLearning-MiniBatchGradientDescent.mp4
8.4 MB
18.4-LargeScaleMachineLearning-StochasticGradientDescentConvergence.mp4
15.1 MB
18.5-LargeScaleMachineLearning-OnlineLearning.mp4
16.7 MB
18.6-LargeScaleMachineLearning-MapReduceAndDataParallelism.mp4
18.1 MB
19.1-ApplicationExamplePhotoOCR-ProblemDescriptionAndPipeline.mp4
9.0 MB
19.2-ApplicationExamplePhotoOCR-SlidingWindows.mp4
18.9 MB
19.3-ApplicationExamplePhotoOCR-GettingLotsOfDataArtificialDataSynthesis.mp4
21.4 MB
19.4-ApplicationExamplePhotoOCR-CeilingAnalysisWhatPartOfThePipelineToWorkOnNext.mp4
18.7 MB
mlclass-ex1.zip
408.7 kB
mlclass-ex2.zip
240.8 kB
mlclass-ex3.zip
7.9 MB
mlclass-ex4.zip
8.0 MB
mlclass-ex5.zip
179.7 kB
mlclass-ex6.zip
915.7 kB
mlclass-ex7.zip
11.5 MB
mlclass-ex8.zip
811.4 kB
octave_session.m
5.3 kB
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