IronPython program to download machine learning course videos to the specified download location. (see below to customize download location)

ml-videos-download.py

# IronPython program to download machine learning course videos to the specified download location.
# (see below to customize download location)
#
# Author: Krishna Padmasola
# Date: 20 Dec 2011

import System;
import System.Net;

# change the value of downloadFolder as appropriate
downloadFolder = 'C:\\Temp\\'

# no need to touch anything below
serverUrl = 'http://download-videos.ml-class.org/cs229/videos/'
sections = [
        { 'title': 'I. INTRODUCTION', 'videos': [ 
 
            { 'title': 'Welcome (7 min)', 'file': '01.1-V3-Introduction-Welcome', 'id': '1', 'viewed': True }, 
            { 'title': 'What is Machine Learning? (7 min)', 'file': '01.2-V2-Introduction-WhatIsMachineLearning', 'id': '2', 'viewed': True }, 
            { 'title': 'Supervised Learning (12 min)', 'file': '01.3-V2-Introduction-SupervisedLearning', 'id': '3', 'viewed': True }, 
            { 'title': 'Unsupervised Learning (14 min)', 'file': '01.4-V2-Introduction-UnsupervisedLearning', 'id': '4', 'viewed': True }
        ]},
        { 'title': 'II. LINEAR REGRESSION WITH ONE VARIABLE', 'videos': [ 
 
            { 'title': 'Model Representation (8 min)', 'file': '02.1-V2-LinearRegressionWithOneVariable-ModelRepresentation', 'id': '5', 'viewed': True }, 
            { 'title': 'Cost Function (8 min)', 'file': '02.2-V2-LinearRegressionWithOneVariable-CostFunction', 'id': '6', 'viewed': True }, 
            { 'title': 'Cost Function - Intuition I (11 min)', 'file': '02.3-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionI', 'id': '7', 'viewed': True }, 
            { 'title': 'Cost Function - Intuition II (9 min)', 'file': '02.4-V2-LinearRegressionWithOneVariable-CostFunctionIntuitionII', 'id': '8', 'viewed': True }, 
            { 'title': 'Gradient Descent (11 min)', 'file': '02.5-V2-LinearRegressionWithOneVariable-GradientDescent', 'id': '9', 'viewed': True }, 
            { 'title': 'Gradient Descent Intuition (12 min)', 'file': '02.6-V2-LinearRegressionWithOneVariable-GradientDescentIntuition', 'id': '10', 'viewed': True }, 
            { 'title': 'Gradient Descent For Linear Regression (10 min)', 'file': '02.7-V2-LinearRegressionWithOneVariable-GradientDescentForLinearRegression', 'id': '11', 'viewed': True }, 
            { 'title': 'What\'s Next (6 min)', 'file': '02.8-V2-What\'sNext', 'id': '12', 'viewed': True }
        ]},
        { 'title': 'III. LINEAR ALGEBRA REVIEW (OPTIONAL)', 'videos': [ 
 
            { 'title': 'Matrices and Vectors (9 min)', 'file': '03.1-V2-LinearAlgebraReview(Optional)-MatricesAndVectors', 'id': '13', 'viewed': True }, 
            { 'title': 'Addition and Scalar Multiplication (7 min)', 'file': '03.2-V2-LinearAlgebraReview(Optional)-AdditionAndScalarMultiplication', 'id': '14', 'viewed': True }, 
            { 'title': 'Matrix Vector Multiplication (14 min)', 'file': '03.3-V2-LinearAlgebraReview(Optional)-MatrixVectorMultiplication', 'id': '15', 'viewed': False }, 
            { 'title': 'Matrix Matrix Multiplication (11 min)', 'file': '03.4-V2-LinearAlgebraReview(Optional)-MatrixMatrixMultiplication', 'id': '16', 'viewed': False }, 
            { 'title': 'Matrix Multiplication Properties (9 min)', 'file': '03.5-V2-LinearAlgebraReview(Optional)-MatrixMultiplicationProperties', 'id': '17', 'viewed': False }, 
            { 'title': 'Inverse and Transpose (11 min)', 'file': '03.6-V2-LinearAlgebraReview(Optional)-InverseAndTranspose', 'id': '18', 'viewed': True }
        ]},
        { 'title': 'IV. LINEAR REGRESSION WITH MULTIPLE VARIABLES', 'videos': [ 
 
            { 'title': 'Multiple Features (8 min)', 'file': '04.1-LinearRegressionWithMultipleVariables-MultipleFeatures', 'id': '19', 'viewed': True }, 
            { 'title': 'Gradient Descent for Multiple Variables (6 min)', 'file': '04.2-LinearRegressionWithMultipleVariables-GradientDescentForMultipleVariables', 'id': '20', 'viewed': True }, 
            { 'title': 'Gradient Descent in Practice I - Feature Scaling (9 min)', 'file': '04.3-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIFeatureScaling', 'id': '21', 'viewed': True }, 
            { 'title': 'Gradient Descent in Practice II - Learning Rate (9 min)', 'file': '04.4-LinearRegressionWithMultipleVariables-GradientDescentInPracticeIILearningRate', 'id': '22', 'viewed': True }, 
            { 'title': 'Features and Polynomial Regression (8 min)', 'file': '04.5-LinearRegressionWithMultipleVariables-FeaturesAndPolynomialRegression', 'id': '23', 'viewed': True }, 
            { 'title': 'Normal Equation (16 min)', 'file': '04.6-V2-LinearRegressionWithMultipleVariables-NormalEquation', 'id': '24', 'viewed': True }, 
            { 'title': 'Normal Equation Noninvertibility (Optional) (6 min)', 'file': '04.7-LinearRegressionWithMultipleVariables-NormalEquationNonInvertibility(Optional)', 'id': '25', 'viewed': True }
        ]},
        { 'title': 'V. OCTAVE TUTORIAL', 'videos': [ 
 
            { 'title': 'Basic Operations (14 min)', 'file': '05.1-OctaveTutorial-BasicOperations', 'id': '26', 'viewed': True }, 
            { 'title': 'Moving Data Around (16 min)', 'file': '05.2-OctaveTutorial-MovingDataAround', 'id': '27', 'viewed': True }, 
            { 'title': 'Computing on Data (13 min)', 'file': '05.3-OctaveTutorial-ComputingOnData', 'id': '28', 'viewed': True }, 
            { 'title': 'Plotting Data (10 min)', 'file': '05.4-OctaveTutorial-PlottingData', 'id': '29', 'viewed': True }, 
            { 'title': 'Control Statements: for, while, if statements (13 min)', 'file': '05.5-OctaveTutorial-ForWhileIfStatementsAndFunctions', 'id': '30', 'viewed': True }, 
            { 'title': 'Vectorization (14 min)', 'file': '05.6-OctaveTutorial-Vectorization', 'id': '31', 'viewed': True }, 
            { 'title': 'Working on and Submitting Programming Exercises (4 min)', 'file': '05.7-OctaveTutorial-WorkingOnAndSubmittingProgrammingExercises', 'id': '32', 'viewed': True }
        ]},
        { 'title': 'VI. LOGISTIC REGRESSION', 'videos': [ 
 
            { 'title': 'Classification (8 min)', 'file': '06.1-LogisticRegression-Classification', 'id': '33', 'viewed': True }, 
            { 'title': 'Hypothesis Representation (7 min)', 'file': '06.2-LogisticRegression-HypothesisRepresentation', 'id': '34', 'viewed': True }, 
            { 'title': 'Decision Boundary (15 min)', 'file': '06.3-LogisticRegression-DecisionBoundary', 'id': '35', 'viewed': True }, 
            { 'title': 'Cost Function (11 min)', 'file': '06.4-LogisticRegression-CostFunction', 'id': '36', 'viewed': True }, 
            { 'title': 'Simplified Cost Function and Gradient Descent (10 min)', 'file': '06.5-LogisticRegression-SimplifiedCostFunctionAndGradientDescent', 'id': '37', 'viewed': True }, 
            { 'title': 'Advanced Optimization (14 min)', 'file': '06.6-LogisticRegression-AdvancedOptimization', 'id': '38', 'viewed': True }, 
            { 'title': 'Multiclass Classification: One-vs-all (6 min)', 'file': '06.7-LogisticRegression-MultiClassClassificationOneVsAll', 'id': '39', 'viewed': True }
        ]},
        { 'title': 'VII. REGULARIZATION', 'videos': [ 
 
            { 'title': 'The Problem of Overfitting', 'file': '07.1-Regularization-TheProblemOfOverfitting', 'id': '41', 'viewed': True }, 
            { 'title': 'Cost Function (10 min)', 'file': '07.2-Regularization-CostFunction', 'id': '42', 'viewed': True }, 
            { 'title': 'Regularized Linear Regression (11 min)', 'file': '07.3-Regularization-RegularizedLinearRegression', 'id': '43', 'viewed': True }, 
            { 'title': 'Regularized Logistic Regression (9 min)', 'file': '07.4-Regularization-RegularizedLogisticRegression', 'id': '44', 'viewed': True }
        ]},
        { 'title': 'VIII. NEURAL NETWORKS: REPRESENTATION', 'videos': [ 
 
            { 'title': 'Non-linear Hypotheses (10 min)', 'file': '08.1-NeuralNetworksRepresentation-NonLinearHypotheses', 'id': '45', 'viewed': True }, 
            { 'title': 'Neurons and the Brain (8 min)', 'file': '08.2-NeuralNetworksRepresentation-NeuronsAndTheBrain', 'id': '46', 'viewed': True }, 
            { 'title': 'Model Representation I (12 min)', 'file': '08.3-NeuralNetworksRepresentation-ModelRepresentationI', 'id': '47', 'viewed': True }, 
            { 'title': 'Model Representation II (12 min)', 'file': '08.4-NeuralNetworksRepresentation-ModelRepresentationII', 'id': '48', 'viewed': True }, 
            { 'title': 'Examples and Intuitions I (7 min)', 'file': '08.5-NeuralNetworksRepresentation-ExamplesAndIntuitionsI', 'id': '49', 'viewed': True }, 
            { 'title': 'Examples and Intuitions II (10 min)', 'file': '08.6-NeuralNetworksRepresentation-ExamplesAndIntuitionsII', 'id': '50', 'viewed': True }, 
            { 'title': 'Multiclass Classification (4 min)', 'file': '08.7-NeuralNetworksRepresentation-MultiClassClassification', 'id': '51', 'viewed': True }
        ]},
        { 'title': 'IX. NEURAL NETWORKS: LEARNING', 'videos': [ 
 
            { 'title': 'Cost Function (7 min)', 'file': '09.1-NeuralNetworksLearning-CostFunction', 'id': '52', 'viewed': True }, 
            { 'title': 'Backpropagation Algorithm (12 min)', 'file': '09.2-NeuralNetworksLearning-BackpropagationAlgorithm', 'id': '53', 'viewed': True }, 
            { 'title': 'Backpropagation Intuition (13 min)', 'file': '09.3-NeuralNetworksLearning-BackpropagationIntuition', 'id': '57', 'viewed': True }, 
            { 'title': 'Implementation Note: Unrolling Parameters (8 min)', 'file': '09.3-NeuralNetworksLearning-ImplementationNoteUnrollingParameters', 'id': '54', 'viewed': True }, 
            { 'title': 'Gradient Checking (8 min)', 'file': '09.4-NeuralNetworksLearning-GradientChecking', 'id': '55', 'viewed': True }, 
            { 'title': 'Random Initialization (7 min)', 'file': '09.5-NeuralNetworksLearning-RandomInitialization', 'id': '56', 'viewed': True }, 
            { 'title': 'Putting It Together (14 min)', 'file': '09.7-NeuralNetworksLearning-PuttingItTogether', 'id': '58', 'viewed': True }, 
            { 'title': 'Autonomous Driving (7 min)', 'file': '09.8-NeuralNetworksLearning-AutonomousDrivingExample', 'id': '59', 'viewed': True }
        ]},
        { 'title': 'X. ADVICE FOR APPLYING MACHINE LEARNING', 'videos': [ 
 
            { 'title': 'Deciding What to Try Next (6 min)', 'file': '10.1-AdviceForApplyingMachineLearning-DecidingWhatToTryNext', 'id': '60', 'viewed': True }, 
            { 'title': 'Evaluating a Hypothesis (8 min)', 'file': '10.2-AdviceForApplyingMachineLearning-EvaluatingAHypothesis', 'id': '61', 'viewed': True }, 
            { 'title': 'Model Selection and Train Validation Test Sets (13 min)', 'file': '10.3-AdviceForApplyingMachineLearning-ModelSelectionAndTrainValidationTestSets', 'id': '62', 'viewed': True }, 
            { 'title': 'Diagnosing Bias vs. Variance (9 min)', 'file': '10.4-AdviceForApplyingMachineLearning-DiagnosingBiasVsVariance', 'id': '63', 'viewed': True }, 
            { 'title': 'Regularization and Bias Variance (12 min)', 'file': '10.5-AdviceForApplyingMachineLearning-RegularizationAndBiasVariance', 'id': '64', 'viewed': True }, 
            { 'title': 'Learning Curves (12 min)', 'file': '10.6-AdviceForApplyingMachineLearning-LearningCurves', 'id': '65', 'viewed': True }, 
            { 'title': 'Deciding What to Do Next Revisited (7 min)', 'file': '10.7-AdviceForApplyingMachineLearning-DecidingWhatToDoNextRevisited', 'id': '66', 'viewed': True }
        ]},
        { 'title': 'XI. MACHINE LEARNING SYSTEM DESIGN', 'videos': [ 
 
            { 'title': 'Prioritzing What to Work On (10 min)', 'file': '11.1-MachineLearningSystemDesign-PrioritizingWhatToWorkOn', 'id': '67', 'viewed': True }, 
            { 'title': 'Error Analysis (13 min)', 'file': '11.2-MachineLearningSystemDesign-ErrorAnalysis', 'id': '68', 'viewed': True }, 
            { 'title': 'Error Metrics for Skewed Classes (12 min)', 'file': '11.3-MachineLearningSystemDesign-ErrorMetricsForSkewedClasses', 'id': '69', 'viewed': True }, 
            { 'title': 'Trading Off Precision and Recall (14 min)', 'file': '11.4-MachineLearningSystemDesign-TradingOffPrecisionAndRecall', 'id': '70', 'viewed': True }, 
            { 'title': 'Data For Machine Learning (11 min)', 'file': '11.5-MachineLearningSystemDesign-DataForMachineLearning', 'id': '71', 'viewed': True }
        ]},
        { 'title': 'XII. SUPPORT VECTOR MACHINES', 'videos': [ 
 
            { 'title': 'Optimization Objective (15 min)', 'file': '12.1-SupportVectorMachines-OptimizationObjective', 'id': '72', 'viewed': True }, 
            { 'title': 'Large Margin Intuition (11 min)', 'file': '12.2-SupportVectorMachines-LargeMarginIntuition', 'id': '73', 'viewed': True }, 
            { 'title': 'Mathematics Behind Large Margin Classification (Optional) (20 min)', 'file': '12.3-SupportVectorMachines-MathematicsBehindLargeMarginClassificationOptional', 'id': '74', 'viewed': True }, 
            { 'title': 'Kernels I (16 min)', 'file': '12.4-SupportVectorMachines-KernelsI', 'id': '75', 'viewed': True }, 
            { 'title': 'Kernels II (16 min)', 'file': '12.5-SupportVectorMachines-KernelsII', 'id': '76', 'viewed': True }, 
            { 'title': 'Using An SVM (21 min)', 'file': '12.6-SupportVectorMachines-UsingAnSVM', 'id': '77', 'viewed': True }
        ]},
        { 'title': 'XIII. CLUSTERING', 'videos': [ 
 
            { 'title': 'Unsupervised Learning: Introduction (3 min)', 'file': '14.1-Clustering-UnsupervisedLearningIntroduction', 'id': '78', 'viewed': True }, 
            { 'title': 'K-Means Algorithm (13 min)', 'file': '14.2-Clustering-KMeansAlgorithm', 'id': '79', 'viewed': True }, 
            { 'title': 'Optimization Objective (7 min)', 'file': '14.3-Clustering-OptimizationObjective', 'id': '80', 'viewed': True }, 
            { 'title': 'Random Initialization (7 min)', 'file': '14.4-Clustering-RandomInitialization', 'id': '81', 'viewed': True }, 
            { 'title': 'Choosing the Number of Clusters (9 min)', 'file': '14.5-Clustering-ChoosingTheNumberOfClusters', 'id': '82', 'viewed': True }
        ]},
        { 'title': 'XIV. DIMENSIONALITY REDUCTION', 'videos': [ 
 
            { 'title': 'Motivation I: Data Compression (10 min)', 'file': '15.1-DimensionalityReduction-MotivationIDataCompression', 'id': '83', 'viewed': True }, 
            { 'title': 'Motivation II: Visualization (6 min)', 'file': '15.2-DimensionalityReduction-MotivationIIVisualization', 'id': '84', 'viewed': True }, 
            { 'title': 'Principal Component Analysis Problem Formulation (9 min)', 'file': '15.3-DimensionalityReduction-PrincipalComponentAnalysisProblemFormulation', 'id': '85', 'viewed': True }, 
            { 'title': 'Principal Component Analysis Algorithm (15 min)', 'file': '15.4-DimensionalityReduction-PrincipalComponentAnalysisAlgorithm', 'id': '86', 'viewed': True }, 
            { 'title': 'Choosing the Number of Principal Components (11 min)', 'file': '15.5-DimensionalityReduction-ChoosingTheNumberOfPrincipalComponents', 'id': '87', 'viewed': True }, 
            { 'title': 'Reconstruction from Compressed Representation (4 min)', 'file': '15.6-DimensionalityReduction-ReconstructionFromCompressedRepresentation', 'id': '89', 'viewed': True }, 
            { 'title': 'Advice for Applying PCA (13 min)', 'file': '15.7-DimensionalityReduction-AdviceForApplyingPCA', 'id': '90', 'viewed': True }
        ]},
        { 'title': 'XV. ANOMALY DETECTION', 'videos': [ 
 
            { 'title': 'Problem Motivation (8 min)', 'file': '16.1-AnomalyDetection-ProblemMotivation-V1', 'id': '91', 'viewed': True }, 
            { 'title': 'Gaussian Distribution (8 min)', 'file': '16.2-AnomalyDetection-GaussianDistribution', 'id': '92', 'viewed': True }, 
            { 'title': 'Algorithm (12 min)', 'file': '16.3-AnomalyDetection-Algorithm', 'id': '94', 'viewed': True }, 
            { 'title': 'Developing and Evaluating an Anomaly Detection System (13 min)', 'file': '16.4-AnomalyDetection-DevelopingAndEvaluatingAnAnomalyDetectionSystem', 'id': '93', 'viewed': True }, 
            { 'title': 'Anomaly Detection vs. Supervised Learning (8 min)', 'file': '16.5-AnomalyDetection-AnomalyDetectionVsSupervisedLearning-V1', 'id': '95', 'viewed': True }, 
            { 'title': 'Choosing What Features to Use (12 min)', 'file': '16.6-AnomalyDetection-ChoosingWhatFeaturesToUse', 'id': '96', 'viewed': True }, 
            { 'title': 'Multivariate Gaussian Distribution (Optional) (14 min)', 'file': '16.7-AnomalyDetection-MultivariateGaussianDistribution-OPTIONAL', 'id': '97', 'viewed': True }, 
            { 'title': 'Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)', 'file': '16.8-AnomalyDetection-AnomalyDetectionUsingTheMultivariateGaussianDistribution-OPTIONAL', 'id': '98', 'viewed': True }
        ]},
        { 'title': 'XVI. RECOMMENDER SYSTEMS', 'videos': [ 
 
            { 'title': 'Problem Formulation (8 min)', 'file': '17.1-RecommenderSystems-ProblemFormulation', 'id': '99', 'viewed': True }, 
            { 'title': 'Content Based Recommendations (15 min)', 'file': '17.2-RecommenderSystems-ContentBasedRecommendations', 'id': '100', 'viewed': True }, 
            { 'title': 'Collaborative Filtering (10 min)', 'file': '17.3-RecommenderSystems-CollaborativeFiltering-V1', 'id': '101', 'viewed': True }, 
            { 'title': 'Collaborative Filtering Algorithm (9 min)', 'file': '17.4-RecommenderSystems-CollaborativeFilteringAlgorithm', 'id': '102', 'viewed': True }, 
            { 'title': 'Vectorization: Low Rank Matrix Factorization (8 min)', 'file': '17.5-RecommenderSystems-VectorizationLowRankMatrixFactorization', 'id': '103', 'viewed': True }, 
            { 'title': 'Implementational Detail: Mean Normalization (9 min)', 'file': '17.6-RecommenderSystems-ImplementationalDetailMeanNormalization', 'id': '104', 'viewed': True }
        ]},
        { 'title': 'XVII. LARGE SCALE MACHINE LEARNING', 'videos': [ 
 
            { 'title': 'Learning With Large Datasets (6 min)', 'file': '18.1-LargeScaleMachineLearning-LearningWithLargeDatasets', 'id': '105', 'viewed': True }, 
            { 'title': 'Stochastic Gradient Descent (13 min)', 'file': '18.2-LargeScaleMachineLearning-StochasticGradientDescent', 'id': '106', 'viewed': True }, 
            { 'title': 'Mini-Batch Gradient Descent (6 min)', 'file': '18.3-LargeScaleMachineLearning-MiniBatchGradientDescent', 'id': '107', 'viewed': True }, 
            { 'title': 'Stochastic Gradient Descent Convergence (12 min)', 'file': '18.4-LargeScaleMachineLearning-StochasticGradientDescentConvergence', 'id': '108', 'viewed': True }, 
            { 'title': 'Online Learning (13 min)', 'file': '18.5-LargeScaleMachineLearning-OnlineLearning', 'id': '109', 'viewed': True }, 
            { 'title': 'Map Reduce and Data Parallelism (15 min)', 'file': '18.6-LargeScaleMachineLearning-MapReduceAndDataParallelism', 'id': '110', 'viewed': True }
        ]},
        { 'title': 'XVIII. APPLICATION EXAMPLE: PHOTO OCR', 'videos': [ 
 
            { 'title': 'Problem Description and Pipeline (7 min)', 'file': '19.1-ApplicationExamplePhotoOCR-ProblemDescriptionAndPipeline', 'id': '111', 'viewed': True }, 
            { 'title': 'Sliding Windows (15 min)', 'file': '19.2-ApplicationExamplePhotoOCR-SlidingWindows', 'id': '112', 'viewed': True }, 
            { 'title': 'Getting Lots of Data and Artificial Data (14 min)', 'file': '19.3-ApplicationExamplePhotoOCR-GettingLotsOfDataArtificialDataSynthesis', 'id': '113', 'viewed': True }, 
            { 'title': 'Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)', 'file': '19.4-ApplicationExamplePhotoOCR-CeilingAnalysisWhatPartOfThePipelineToWorkOnNext', 'id': '114', 'viewed': False }
        ]},
        { 'title': 'XIX. CONCLUSION', 'videos': [ 
 
            { 'title': 'Summary and Thank You (5 min)', 'file': '20.1-Conclusion-SummaryAndThankYou', 'id': '115', 'viewed': True }
        ]}]; 

if __name__=='__main__':
    webclient = System.Net.WebClient()
    for section in sections:
        for video in section['videos']:
            filename = video['file'] + '.mp4'
            destinationFileName = downloadFolder + filename
            sourceFileName = serverUrl + filename
            print 'Downloading ' + sourceFileName + '...'
            webclient.DownloadFile(sourceFileName, destinationFileName)
            print 'Done!'
    print 'All downloads completed!'

This IronPython script downloads the lecture videos from Prof. Andrew Ng's Machine Learning class of Fall 2011 (http://ml-class.org). Basically I massaged the source of http://www.ml-class.org/course/video/list?mode=download a wee bit to convert JSON data structures into python data structures, and the rest was straightforward. You should be able to convert it regular Python script fairly easily, if required. I used IronPython as I have a Windows laptop and Visual Studio has a great IDE for editing Python scripts (http://pytools.codeplex.com/). Let me know if you find this script useful. Enjoy :)