ML-Class_videos
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2011-11-6 01:31
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2024-11-5 20:24
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62
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708.17 MB
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57
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- 05.2-OctaveTutorial-MovingDataAround.mp425.42MB
- 06.6-LogisticRegression-AdvancedOptimization.mp421.59MB
- 09.8-NeuralNetworksLearning-AutonomousDrivingExample.mp421.25MB
- 05.1-OctaveTutorial-BasicOperations.mp420.69MB
- 05.5-OctaveTutorial-ForWhileIfStatementsAndFunctions.mp419.69MB
- 01.4-V2-Introduction-UnsupervisedLearning.mp418.17MB
- 09.7-NeuralNetworksLearning-PuttingItTogether.mp417.88MB
- 06.3-LogisticRegression-DecisionBoundary.mp417.51MB
- 09.3-NeuralNetworksLearning-BackpropagationIntuition.mp417.14MB
- 08.6-NeuralNetworksRepresentation-ExamplesAndIntuitionsII.mp416.84MB
- 05.6-OctaveTutorial-Vectorization.mp416.83MB
- 03.3-V2-LinearAlgebraReview(Optional)-MatrixVectorMultiplication.mp415.9MB
- 09.2-NeuralNetworksLearning-BackpropagationAlgorithm.mp415.07MB
- 02.5-V2-LinearRegressionWithOneVariable-GradientDescent.mp414.93MB
- 09.4-NeuralNetworksLearning-GradientChecking.mp414.76MB
- 08.4-NeuralNetworksRepresentation-ModelRepresentationII.mp414.41MB
- 08.3-NeuralNetworksRepresentation-ModelRepresentationI.mp414.37MB
- 03.6-V2-LinearAlgebraReview(Optional)-InverseAndTranspose.mp414.13MB
- 06.4-LogisticRegression-CostFunction.mp414.11MB
- 02.4-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionII.mp413.92MB
- 02.6-V2-LinearRegressionWithOneVariable-GradientDescentIntuition.mp413.91MB
- 03.4-V2-LinearAlgebraReview(Optional)-MatrixMatrixMultiplication.mp413.81MB
- 01.3-V2-Introduction-SupervisedLearning.mp413.65MB
- 02.7-V2-LinearRegressionWithOneVariable-GradientDescentForLinearRegression.mp413.55MB
- 07.4-Regularization-RegularizedLogisticRegression.mp413.5MB
- 04.6-V2-LinearRegressionWithMultipleVariables-NormalEquation.mp413.34MB
- 06.5-LogisticRegression-SimplifiedCostFunctionAndGradientDescent.mp413.07MB
- 02.3-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionI.mp412.91MB
- 07.3-Regularization-RegularizedLinearRegression.mp412.77MB
- 07.2-Regularization-CostFunction.mp412.43MB
- 07.1-Regularization-TheProblemOfOverfitting.mp411.96MB
- 08.1-NeuralNetworksRepresentation-NonLinearHypotheses.mp411.53MB
- 08.2-NeuralNetworksRepresentation-NeuronsAndTheBrain.mp411.47MB
- 01.2-V2-Introduction-WhatIsMachineLearning.mp411.44MB
- 05.4-OctaveTutorial-PlottingData.mp411.31MB
- 09.3-NeuralNetworksLearning-ImplementationNoteUnrollingParameters.mp410.54MB
- 05.3-OctaveTutorial-ComputingOnData.mp410.37MB
- 03.5-V2-LinearAlgebraReview(Optional)-MatrixMultiplicationProperties.mp410.16MB
- 03.1-V2-LinearAlgebraReview(Optional)-MatricesAndVectors.mp49.79MB
- 02.2-V2-LinearRegressionWithOneVariable-CostFunction.mp49.63MB
- 02.1-V2-LinearRegressionWithOneVariable-ModelRepresentation.mp49.49MB
- 06.2-LogisticRegression-HypothesisRepresentation.mp48.81MB
- 06.1-LogisticRegression-Classification.mp48.73MB
- 08.5-NeuralNetworksRepresentation-ExamplesAndIntuitionsI.mp48.29MB
- 09.1-NeuralNetworksLearning-CostFunction.mp48.1MB
- 09.5-NeuralNetworksLearning-RandomInitialization.mp47.95MB
- 03.2-V2-LinearAlgebraReview(Optional)-AdditionAndScalarMultiplication.mp47.85MB
- 04.3-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIFeatureScaling.mp47.58MB
- 06.7-LogisticRegression-MultiClassClassificationOneVsAll.mp47.29MB
- 05.7-OctaveTutorial-WorkingOnAndSubmittingProgrammingExercises.mp47.25MB
- 04.4-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIILearningRate.mp46.86MB
- 04.1-LinearRegressionWithMultipleVariables-MultipleFeatures.mp46.13MB
- 02.8-V2-What'sNext.mp46.09MB
- 04.2-LinearRegressionWithMultipleVariables-GradientDescentForMultipleVariables.mp45.9MB
- 04.5-LinearRegressionWithMultipleVariables-FeaturesAndPolynomialRegression.mp45.74MB
- 04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional).mp45.18MB
- 04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional) (1).mp45.18MB
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