zhongziso种子搜
首页
功能
磁力转BT
BT转磁力
使用教程
免责声明
关于
zhongziso
搜索
Machine Learning - Stanford
magnet:?xt=urn:btih:3B33CB59C493ED3468B81E2DD388419482C16F39&dn=Machine Learning - Stanford
磁力链接详情
Hash值:
3B33CB59C493ED3468B81E2DD388419482C16F39
点击数:
63
文件大小:
1.62 GB
文件数量:
113
创建日期:
2011-12-28 18:22
最后访问:
2024-7-20 13:28
访问标签:
Machine
Learning
-
Stanford
文件列表详情
01.2-V2-Introduction-WhatIsMachineLearning.mp4 30.4 MB
01.3-V2-Introduction-SupervisedLearning.mp4 15.45 MB
01.4-V2-Introduction-UnsupervisedLearning.mp4 38.56 MB
02.1-V2-LinearRegressionWithOneVariable-ModelRepresentation.mp4 11.61 MB
02.2-V2-LinearRegressionWithOneVariable-CostFunction.mp4 13.08 MB
02.3-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionI.mp4 16.3 MB
02.4-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionII.mp4 31.62 MB
02.5-V2-LinearRegressionWithOneVariable-GradientDescent.mp4 27 MB
02.6-V2-LinearRegressionWithOneVariable-GradientDescentIntuition.mp4 18.92 MB
02.7-V2-LinearRegressionWithOneVariable-GradientDescentForLinearRegression.mp4 25.47 MB
02.8-V2-What'sNext.mp4 7.3 MB
03.1-V2-LinearAlgebraReview(Optional)-MatricesAndVectors.mp4 11.92 MB
03.2-V2-LinearAlgebraReview(Optional)-AdditionAndScalarMultiplication.mp4 9.22 MB
03.3-V2-LinearAlgebraReview(Optional)-MatrixVectorMultiplication.mp4 20.23 MB
03.4-V2-LinearAlgebraReview(Optional)-MatrixMatrixMultiplication.mp4 22.35 MB
03.5-V2-LinearAlgebraReview(Optional)-MatrixMultiplicationProperties.mp4 11.77 MB
03.6-V2-LinearAlgebraReview(Optional)-InverseAndTranspose.mp4 24.6 MB
04.1-LinearRegressionWithMultipleVariables-MultipleFeatures.mp4 6.13 MB
04.2-LinearRegressionWithMultipleVariables-GradientDescentForMultipleVariables.mp4 5.9 MB
04.3-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIFeatureScaling.mp4 7.58 MB
04.4-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIILearningRate.mp4 6.86 MB
04.5-LinearRegressionWithMultipleVariables-FeaturesAndPolynomialRegression.mp4 5.74 MB
04.6-V2-LinearRegressionWithMultipleVariables-NormalEquation.mp4 13.34 MB
04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional).mp4 5.18 MB
05.1-OctaveTutorial-BasicOperations.mp4 20.69 MB
05.2-OctaveTutorial-MovingDataAround.mp4 25.42 MB
05.3-OctaveTutorial-ComputingOnData.mp4 10.37 MB
05.4-OctaveTutorial-PlottingData.mp4 11.31 MB
05.5-OctaveTutorial-ForWhileIfStatementsAndFunctions.mp4 19.69 MB
05.6-OctaveTutorial-Vectorization.mp4 16.83 MB
05.7-OctaveTutorial-WorkingOnAndSubmittingProgrammingExercises.mp4 7.25 MB
06.1-LogisticRegression-Classification.mp4 8.73 MB
06.2-LogisticRegression-HypothesisRepresentation.mp4 8.81 MB
06.3-LogisticRegression-DecisionBoundary.mp4 17.51 MB
06.4-LogisticRegression-CostFunction.mp4 14.11 MB
06.5-LogisticRegression-SimplifiedCostFunctionAndGradientDescent.mp4 13.07 MB
06.6-LogisticRegression-AdvancedOptimization.mp4 21.59 MB
06.7-LogisticRegression-MultiClassClassificationOneVsAll.mp4 7.29 MB
07.1-Regularization-TheProblemOfOverfitting.mp4 11.96 MB
07.2-Regularization-CostFunction.mp4 12.43 MB
07.3-Regularization-RegularizedLinearRegression.mp4 12.77 MB
07.4-Regularization-RegularizedLogisticRegression.mp4 13.5 MB
08.1-NeuralNetworksRepresentation-NonLinearHypotheses.mp4 11.53 MB
08.2-NeuralNetworksRepresentation-NeuronsAndTheBrain.mp4 11.47 MB
08.3-NeuralNetworksRepresentation-ModelRepresentationI.mp4 14.37 MB
08.4-NeuralNetworksRepresentation-ModelRepresentationII.mp4 14.41 MB
08.5-NeuralNetworksRepresentation-ExamplesAndIntuitionsI.mp4 8.29 MB
08.6-NeuralNetworksRepresentation-ExamplesAndIntuitionsII.mp4 16.84 MB
08.7-NeuralNetworksRepresentation-MultiClassClassification.mp4 5.41 MB
09.1-NeuralNetworksLearning-CostFunction.mp4 8.1 MB
09.2-NeuralNetworksLearning-BackpropagationAlgorithm.mp4 15.07 MB
09.3-NeuralNetworksLearning-BackpropagationIntuition.mp4 17.14 MB
09.3-NeuralNetworksLearning-ImplementationNoteUnrollingParameters.mp4 10.54 MB
09.4-NeuralNetworksLearning-GradientChecking.mp4 14.76 MB
09.5-NeuralNetworksLearning-RandomInitialization.mp4 7.95 MB
09.7-NeuralNetworksLearning-PuttingItTogether.mp4 17.88 MB
09.8-NeuralNetworksLearning-AutonomousDrivingExample.mp4 21.25 MB
10.1-AdviceForApplyingMachineLearning-DecidingWhatToTryNext.mp4 7.58 MB
10.2-AdviceForApplyingMachineLearning-EvaluatingAHypothesis.mp4 9.52 MB
10.3-AdviceForApplyingMachineLearning-ModelSelectionAndTrainValidationTestSets.mp4 16.13 MB
10.4-AdviceForApplyingMachineLearning-DiagnosingBiasVsVariance.mp4 10.42 MB
10.5-AdviceForApplyingMachineLearning-RegularizationAndBiasVariance.mp4 13.87 MB
10.6-AdviceForApplyingMachineLearning-LearningCurves.mp4 13.54 MB
10.7-AdviceForApplyingMachineLearning-DecidingWhatToDoNextRevisited.mp4 8.94 MB
11.1-MachineLearningSystemDesign-PrioritizingWhatToWorkOn.mp4 12.32 MB
11.2-MachineLearningSystemDesign-ErrorAnalysis.mp4 16.94 MB
11.3-MachineLearningSystemDesign-ErrorMetricsForSkewedClasses.mp4 14.24 MB
11.4-MachineLearningSystemDesign-TradingOffPrecisionAndRecall.mp4 17.29 MB
11.5-MachineLearningSystemDesign-DataForMachineLearning.mp4 13.98 MB
12.1-SupportVectorMachines-OptimizationObjective.mp4 17.77 MB
12.2-SupportVectorMachines-LargeMarginIntuition.mp4 12.66 MB
12.3-SupportVectorMachines-MathematicsBehindLargeMarginClassificationOptional.mp4 22.91 MB
12.4-SupportVectorMachines-KernelsI.mp4 18.74 MB
12.5-SupportVectorMachines-KernelsII.mp4 18.31 MB
12.6-SupportVectorMachines-UsingAnSVM.mp4 25.76 MB
14.1-Clustering-UnsupervisedLearningIntroduction.mp4 4.12 MB
14.2-Clustering-KMeansAlgorithm.mp4 14.67 MB
14.3-Clustering-OptimizationObjective.mp4 8.78 MB
14.4-Clustering-RandomInitialization.mp4 9.31 MB
14.5-Clustering-ChoosingTheNumberOfClusters.mp4 10.11 MB
15.1-DimensionalityReduction-MotivationIDataCompression.mp4 17.63 MB
15.2-DimensionalityReduction-MotivationIIVisualization.mp4 6.91 MB
15.3-DimensionalityReduction-PrincipalComponentAnalysisProblemFormulation.mp4 11.4 MB
15.4-DimensionalityReduction-PrincipalComponentAnalysisAlgorithm.mp4 19.4 MB
15.5-DimensionalityReduction-ChoosingTheNumberOfPrincipalComponents.mp4 12.47 MB
15.6-DimensionalityReduction-ReconstructionFromCompressedRepresentation.mp4 5.93 MB
15.7-DimensionalityReduction-AdviceForApplyingPCA.mp4 15.8 MB
16.1-AnomalyDetection-ProblemMotivation-V1.mp4 8.83 MB
16.2-AnomalyDetection-GaussianDistribution.mp4 12.88 MB
16.3-AnomalyDetection-Algorithm.mp4 15.3 MB
16.4-AnomalyDetection-DevelopingAndEvaluatingAnAnomalyDetectionSystem.mp4 16.92 MB
16.5-AnomalyDetection-AnomalyDetectionVsSupervisedLearning-V1.mp4 10.79 MB
16.6-AnomalyDetection-ChoosingWhatFeaturesToUse.mp4 15.43 MB
16.7-AnomalyDetection-MultivariateGaussianDistribution-OPTIONAL.mp4 17.27 MB
16.8-AnomalyDetection-AnomalyDetectionUsingTheMultivariateGaussianDistribution-OPTIONAL.mp4 17.75 MB
17.1-RecommenderSystems-ProblemFormulation.mp4 13.65 MB
17.2-RecommenderSystems-ContentBasedRecommendations.mp4 18.73 MB
17.3-RecommenderSystems-CollaborativeFiltering-V1.mp4 13.1 MB
17.4-RecommenderSystems-CollaborativeFilteringAlgorithm.mp4 11.44 MB
17.5-RecommenderSystems-VectorizationLowRankMatrixFactorization.mp4 10.45 MB
17.6-RecommenderSystems-ImplementationalDetailMeanNormalization.mp4 10.46 MB
18.1-LargeScaleMachineLearning-LearningWithLargeDatasets.mp4 7.12 MB
18.2-LargeScaleMachineLearning-StochasticGradientDescent.mp4 16.4 MB
18.3-LargeScaleMachineLearning-MiniBatchGradientDescent.mp4 7.99 MB
18.4-LargeScaleMachineLearning-StochasticGradientDescentConvergence.mp4 14.41 MB
18.5-LargeScaleMachineLearning-OnlineLearning.mp4 15.96 MB
18.6-LargeScaleMachineLearning-MapReduceAndDataParallelism.mp4 17.3 MB
19.1-ApplicationExamplePhotoOCR-ProblemDescriptionAndPipeline.mp4 8.54 MB
19.2-ApplicationExamplePhotoOCR-SlidingWindows.mp4 10.1 MB
19.3-ApplicationExamplePhotoOCR-GettingLotsOfDataArtificialDataSynthesis.mp4 8.53 MB
19.4-ApplicationExamplePhotoOCR-CeilingAnalysisWhatPartOfThePipelineToWorkOnNext.mp4 10.64 MB
20.1-Conclusion-SummaryAndThankYou.mp4 4.52 MB
Octave-3.2.4_i686-pc-mingw32_gcc-4.4.0_setup.exe 69.61 MB
其他位置