Machine Learning Stanford | 3B33CB59C493ED3468B81E2DD388419482C16F39

Machine Learning Stanford

Name	Machine Learning - Stanford	DOWNLOAD Copy Link
Total Size	1.7 GB
Total Files	132
Last Seen	2024-09-19 02:58
Hash	3B33CB59C493ED3468B81E2DD388419482C16F39

/Self-notes/
08-10.txt	0.1 KB
12-10.txt	0.7 KB
22-11.txt	0.0 KB
Lecture1.pdf	4.9 MB
Lecture10.pdf	1.6 MB
Lecture11.pdf	509.6 KB
Lecture12.pdf	2.4 MB
Lecture13.pdf	2.3 MB
Lecture14.pdf	1.7 MB
Lecture15.pdf	3.5 MB
Lecture16.pdf	1.5 MB
Lecture2.pdf	3.0 MB
Lecture3.pdf	1.9 MB
Lecture4.pdf	1.8 MB
Lecture6.pdf	1.9 MB
Lecture7.pdf	1.5 MB
Lecture8.pdf	5.5 MB
Lecture9.pdf	3.5 MB
octave_session.m	5.3 KB
/
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	6.2 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
09.3-NeuralNetworksLearning-ImplementationNoteUnrollingParameters.mp4	11.1 MB
09.4-NeuralNetworksLearning-GradientChecking.mp4	15.5 MB
09.5-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	15.4 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	10.6 MB
19.3-ApplicationExamplePhotoOCR-GettingLotsOfDataArtificialDataSynthesis.mp4	8.9 MB
19.4-ApplicationExamplePhotoOCR-CeilingAnalysisWhatPartOfThePipelineToWorkOnNext.mp4	11.2 MB
20.1-Conclusion-SummaryAndThankYou.mp4	4.7 MB
Octave-3.2.4_i686-pc-mingw32_gcc-4.4.0_setup.exe	73.0 MB
Total files 132