magnet:?xt=urn:btih:E0CBFC2036333C0FB1A96BFB0A103AE650E6CCC5
12_XII._Support_Vector_Machines_Week_7/06_Using_An_SVM_21_min.ogv 68.8 MB12_XII._Support_Vector_Machines_Week_7/03_Mathematics_Behind_Large_Margin_Classification_Optional_20_min.ogv 57.2 MB18_XVIII._Application_Example-_Photo_OCR/03_Getting_Lots_of_Data_and_Artificial_Data_16_min.ogv 55.6 MB17_XVII._Large_Scale_Machine_Learning_Week_10/05_Online_Learning_13_min.ogv 54.2 MB15_XV._Anomaly_Detection_Week_9/08_Anomaly_Detection_using_the_Multivariate_Gaussian_Distribution_Optional_14_min.ogv 52.5 MB14_XIV._Dimensionality_Reduction_Week_8/04_Principal_Component_Analysis_Algorithm_15_min.ogv 51.4 MB16_XVI._Recommender_Systems_Week_9/02_Content_Based_Recommendations_15_min.ogv 51.3 MB09_IX._Neural_Networks-_Learning_Week_5/07_Putting_It_Together_14_min.ogv 50.9 MB06_VI._Logistic_Regression_Week_3/06_Advanced_Optimization_14_min.ogv 49.5 MB11_XI._Machine_Learning_System_Design_Week_6/02_Error_Analysis_13_min.ogv 49.3 MB09_IX._Neural_Networks-_Learning_Week_5/03_Backpropagation_Intuition_13_min.ogv 48.6 MB05_V._Octave_Tutorial_Week_2/02_Moving_Data_Around_16_min.ogv 47.9 MB12_XII._Support_Vector_Machines_Week_7/05_Kernels_II_16_min.ogv 47.0 MB05_V._Octave_Tutorial_Week_2/06_Vectorization_14_min.ogv 46.4 MB17_XVII._Large_Scale_Machine_Learning_Week_10/02_Stochastic_Gradient_Descent_13_min.ogv 46.0 MB01_I._Introduction_Week_1/04_Unsupervised_Learning_14_min.ogv 45.8 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/06_Normal_Equation_16_min.ogv 45.7 MB14_XIV._Dimensionality_Reduction_Week_8/07_Advice_for_Applying_PCA_13_min.ogv 45.1 MB18_XVIII._Application_Example-_Photo_OCR/04_Ceiling_Analysis-_What_Part_of_the_Pipeline_to_Work_on_Next_14_min.ogv 45.0 MB06_VI._Logistic_Regression_Week_3/03_Decision_Boundary_15_min.ogv 43.4 MB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.ogv 43.1 MB11_XI._Machine_Learning_System_Design_Week_6/04_Trading_Off_Precision_and_Recall_14_min.ogv 43.0 MB15_XV._Anomaly_Detection_Week_9/04_Developing_and_Evaluating_an_Anomaly_Detection_System_13_min.ogv 42.9 MB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.ogv 42.5 MB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.pptx 42.3 MB15_XV._Anomaly_Detection_Week_9/07_Multivariate_Gaussian_Distribution_Optional_14_min.ogv 41.7 MB05_V._Octave_Tutorial_Week_2/05_Control_Statements-_for_while_if_statements_13_min.ogv 41.4 MB09_IX._Neural_Networks-_Learning_Week_5/02_Backpropagation_Algorithm_12_min.ogv 41.2 MB17_XVII._Large_Scale_Machine_Learning_Week_10/06_Map_Reduce_and_Data_Parallelism_14_min.ogv 40.5 MB08_VIII._Neural_Networks-_Representation_Week_4/04_Model_Representation_II_12_min.ogv 40.4 MB12_XII._Support_Vector_Machines_Week_7/04_Kernels_I_16_min.ogv 40.0 MB05_V._Octave_Tutorial_Week_2/04_Plotting_Data_10_min.ogv 40.0 MB15_XV._Anomaly_Detection_Week_9/06_Choosing_What_Features_to_Use_12_min.ogv 39.7 MB17_XVII._Large_Scale_Machine_Learning_Week_10/04_Stochastic_Gradient_Descent_Convergence_12_min.ogv 39.1 MB18_XVIII._Application_Example-_Photo_OCR/02_Sliding_Windows_15_min.ogv 38.2 MB08_VIII._Neural_Networks-_Representation_Week_4/03_Model_Representation_I_12_min.ogv 38.0 MB15_XV._Anomaly_Detection_Week_9/03_Algorithm_12_min.ogv 37.9 MB09_IX._Neural_Networks-_Learning_Week_5/05_Gradient_Checking_12_min.ogv 37.7 MB11_XI._Machine_Learning_System_Design_Week_6/05_Data_For_Machine_Learning_11_min.ogv 37.4 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/03_Model_Selection_and_Train-Validation-Test_Sets_12_min.ogv 37.1 MB11_XI._Machine_Learning_System_Design_Week_6/03_Error_Metrics_for_Skewed_Classes_12_min.ogv 37.0 MB16_XVI._Recommender_Systems_Week_9/04_Collaborative_Filtering_Algorithm_9_min.ogv 36.8 MB03_III._Linear_Algebra_Review_Week_1_Optional/03_Matrix_Vector_Multiplication_14_min.ogv 36.7 MB02_II._Linear_Regression_with_One_Variable_Week_1/05_Gradient_Descent_11_min.ogv 36.6 MB14_XIV._Dimensionality_Reduction_Week_8/05_Choosing_the_Number_of_Principal_Components_11_min.ogv 35.6 MB05_V._Octave_Tutorial_Week_2/03_Computing_on_Data_13_min.ogv 35.0 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/05_Regularization_and_Bias-Variance_11_min.ogv 33.9 MB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.ogv 32.8 MB03_III._Linear_Algebra_Review_Week_1_Optional/06_Inverse_and_Transpose_11_min.ogv 32.1 MB13_XIII._Clustering_Week_8/02_K-Means_Algorithm_13_min.ogv 32.0 MB07_VII._Regularization_Week_3/04_Regularized_Logistic_Regression_9_min.ogv 31.9 MB01_I._Introduction_Week_1/03_Supervised_Learning_12_min.ogv 31.8 MB02_II._Linear_Regression_with_One_Variable_Week_1/03_Cost_Function_-_Intuition_I_11_min.ogv 31.8 MB08_VIII._Neural_Networks-_Representation_Week_4/06_Examples_and_Intuitions_II_10_min.ogv 31.6 MB02_II._Linear_Regression_with_One_Variable_Week_1/06_Gradient_Descent_Intuition_12_min.ogv 31.4 MB02_II._Linear_Regression_with_One_Variable_Week_1/04_Cost_Function_-_Intuition_II_9_min.ogv 31.1 MB06_VI._Logistic_Regression_Week_3/04_Cost_Function_11_min.ogv 31.0 MB06_VI._Logistic_Regression_Week_3/05_Simplified_Cost_Function_and_Gradient_Descent_10_min.ogv 30.4 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/06_Learning_Curves_12_min.ogv 30.0 MB03_III._Linear_Algebra_Review_Week_1_Optional/04_Matrix_Matrix_Multiplication_11_min.ogv 29.5 MB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.ogv 29.5 MB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.ogv 29.3 MB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.ogv 29.0 MB01_I._Introduction_Week_1/01_Welcome_7_min.ogv 28.6 MB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.ogv 28.5 MB16_XVI._Recommender_Systems_Week_9/03_Collaborative_Filtering_10_min.ogv 28.5 MB02_II._Linear_Regression_with_One_Variable_Week_1/07_Gradient_Descent_For_Linear_Regression_10_min.ogv 28.2 MB07_VII._Regularization_Week_3/02_Cost_Function_10_min.ogv 28.2 MB16_XVI._Recommender_Systems_Week_9/06_Implementational_Detail-_Mean_Normalization_9_min.ogv 28.0 MB15_XV._Anomaly_Detection_Week_9/05_Anomaly_Detection_vs._Supervised_Learning_8_min.ogv 27.9 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/07_Deciding_What_to_Do_Next_Revisited_7_min.ogv 27.0 MB08_VIII._Neural_Networks-_Representation_Week_4/02_Neurons_and_the_Brain_8_min.ogv 26.7 MB09_IX._Neural_Networks-_Learning_Week_5/08_Autonomous_Driving_7_min.ogv 26.5 MB07_VII._Regularization_Week_3/03_Regularized_Linear_Regression_11_min.ogv 26.3 MB14_XIV._Dimensionality_Reduction_Week_8/03_Principal_Component_Analysis_Problem_Formulation_9_min.ogv 26.3 MB09_IX._Neural_Networks-_Learning_Week_5/04_Implementation_Note-_Unrolling_Parameters_8_min.ogv 26.1 MB01_I._Introduction_Week_1/02_What_is_Machine_Learning_7_min.ogv 26.1 MB12_XII._Support_Vector_Machines_Week_7/02_Large_Margin_Intuition_11_min.ogv 25.7 MB
12_XII._Support_Vector_Machines_Week_7/06_Using_An_SVM_21_min.mp4 25.1 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/04_Gradient_Descent_in_Practice_II_-_Learning_Rate_9_min.ogv 25.0 MB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.ogv 24.9 MB13_XIII._Clustering_Week_8/03_Optimization_Objective_7_min.ogv 24.1 MB16_XVI._Recommender_Systems_Week_9/05_Vectorization-_Low_Rank_Matrix_Factorization_8_min.ogv 24.0 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/03_Gradient_Descent_in_Practice_I_-_Feature_Scaling_9_min.ogv 24.0 MB13_XIII._Clustering_Week_8/05_Choosing_the_Number_of_Clusters_8_min.ogv 23.7 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/04_Diagnosing_Bias_vs._Variance_8_min.ogv 23.6 MB15_XV._Anomaly_Detection_Week_9/02_Gaussian_Distribution_10_min.ogv 22.9 MB12_XII._Support_Vector_Machines_Week_7/03_Mathematics_Behind_Large_Margin_Classification_Optional_20_min.mp4 22.9 MB02_II._Linear_Regression_with_One_Variable_Week_1/02_Cost_Function_8_min.ogv 22.7 MB06_VI._Logistic_Regression_Week_3/02_Hypothesis_Representation_7_min.ogv 22.5 MB03_III._Linear_Algebra_Review_Week_1_Optional/05_Matrix_Multiplication_Properties_9_min.ogv 22.4 MB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.ogv 22.3 MB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.ogv 22.1 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.ogv 22.0 MB05_V._Octave_Tutorial_Week_2/02_Moving_Data_Around_16_min.mp4 21.8 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/02_Evaluating_a_Hypothesis_8_min.ogv 21.3 MB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.ogv 20.6 MB09_IX._Neural_Networks-_Learning_Week_5/06_Random_Initialization_7_min.ogv 20.3 MB13_XIII._Clustering_Week_8/04_Random_Initialization_8_min.ogv 20.0 MB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.ogv 19.9 MB18_XVIII._Application_Example-_Photo_OCR/03_Getting_Lots_of_Data_and_Artificial_Data_16_min.mp4 19.7 MB
02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min_jp2.zip 19.4 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.ogv 19.2 MB06_VI._Logistic_Regression_Week_3/06_Advanced_Optimization_14_min.mp4 19.0 MB08_VIII._Neural_Networks-_Representation_Week_4/05_Examples_and_Intuitions_I_7_min.ogv 18.7 MB14_XIV._Dimensionality_Reduction_Week_8/04_Principal_Component_Analysis_Algorithm_15_min.mp4 18.7 MB17_XVII._Large_Scale_Machine_Learning_Week_10/03_Mini-Batch_Gradient_Descent_6_min.ogv 18.6 MB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.mp4 18.6 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/07_Normal_Equation_Noninvertibility_Optional_6_min.ogv 18.5 MB12_XII._Support_Vector_Machines_Week_7/04_Kernels_I_16_min.mp4 18.4 MB12_XII._Support_Vector_Machines_Week_7/05_Kernels_II_16_min.mp4 18.3 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/05_Features_and_Polynomial_Regression_8_min.ogv 18.0 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/06_Normal_Equation_16_min.mp4 18.0 MB16_XVI._Recommender_Systems_Week_9/02_Content_Based_Recommendations_15_min.mp4 17.8 MB06_VI._Logistic_Regression_Week_3/03_Decision_Boundary_15_min.mp4 17.6 MB01_I._Introduction_Week_1/04_Unsupervised_Learning_14_min.mp4 17.5 MB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.mp4 17.5 MB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.ogv 17.3 MB18_XVIII._Application_Example-_Photo_OCR/02_Sliding_Windows_15_min.mp4 17.3 MB05_V._Octave_Tutorial_Week_2/05_Control_Statements-_for_while_if_statements_13_min.mp4 17.3 MB15_XV._Anomaly_Detection_Week_9/08_Anomaly_Detection_using_the_Multivariate_Gaussian_Distribution_Optional_14_min.mp4 17.1 MB09_IX._Neural_Networks-_Learning_Week_5/07_Putting_It_Together_14_min.mp4 17.1 MB18_XVIII._Application_Example-_Photo_OCR/04_Ceiling_Analysis-_What_Part_of_the_Pipeline_to_Work_on_Next_14_min.mp4 16.9 MB05_V._Octave_Tutorial_Week_2/06_Vectorization_14_min.mp4 16.9 MB17_XVII._Large_Scale_Machine_Learning_Week_10/06_Map_Reduce_and_Data_Parallelism_14_min.mp4 16.8 MB11_XI._Machine_Learning_System_Design_Week_6/04_Trading_Off_Precision_and_Recall_14_min.mp4 16.8 MB02_II._Linear_Regression_with_One_Variable_Week_1/08_Whats_Next_6_min.ogv 16.8 MB15_XV._Anomaly_Detection_Week_9/07_Multivariate_Gaussian_Distribution_Optional_14_min.mp4 16.7 MB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min_jp2.zip 16.6 MB03_III._Linear_Algebra_Review_Week_1_Optional/02_Addition_and_Scalar_Multiplication_7_min.ogv 16.2 MB09_IX._Neural_Networks-_Learning_Week_5/03_Backpropagation_Intuition_13_min.mp4 16.2 MB14_XIV._Dimensionality_Reduction_Week_8/02_Motivation_II-_Visualization_6_min.ogv 16.2 MB11_XI._Machine_Learning_System_Design_Week_6/02_Error_Analysis_13_min.mp4 16.2 MB17_XVII._Large_Scale_Machine_Learning_Week_10/02_Stochastic_Gradient_Descent_13_min.mp4 16.1 MB05_V._Octave_Tutorial_Week_2/03_Computing_on_Data_13_min.mp4 16.0 MB15_XV._Anomaly_Detection_Week_9/04_Developing_and_Evaluating_an_Anomaly_Detection_System_13_min.mp4 15.9 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/02_Gradient_Descent_for_Multiple_Variables_5_min.ogv 15.8 MB03_III._Linear_Algebra_Review_Week_1_Optional/03_Matrix_Vector_Multiplication_14_min.mp4 15.7 MB05_V._Octave_Tutorial_Week_2/07_Working_on_and_Submitting_Programming_Exercises_4_min.ogv 15.7 MB17_XVII._Large_Scale_Machine_Learning_Week_10/05_Online_Learning_13_min.mp4 15.6 MB09_IX._Neural_Networks-_Learning_Week_5/08_Autonomous_Driving_7_min.mp4 15.6 MB19_XIX._Conclusion/01_Summary_and_Thank_You_5_min.ogv 15.4 MB14_XIV._Dimensionality_Reduction_Week_8/07_Advice_for_Applying_PCA_13_min.mp4 15.4 MB06_VI._Logistic_Regression_Week_3/07_Multiclass_Classification-_One-vs-all_6_min.ogv 15.2 MB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.mp4 15.0 MB08_VIII._Neural_Networks-_Representation_Week_4/07_Multiclass_Classification_4_min.ogv 14.9 MB15_XV._Anomaly_Detection_Week_9/06_Choosing_What_Features_to_Use_12_min.mp4 14.8 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/03_Model_Selection_and_Train-Validation-Test_Sets_12_min.mp4 14.8 MB08_VIII._Neural_Networks-_Representation_Week_4/06_Examples_and_Intuitions_II_10_min.mp4 14.7 MB15_XV._Anomaly_Detection_Week_9/03_Algorithm_12_min.mp4 14.6 MB09_IX._Neural_Networks-_Learning_Week_5/02_Backpropagation_Algorithm_12_min.mp4 14.6 MB13_XIII._Clustering_Week_8/02_K-Means_Algorithm_13_min.mp4 14.5 MB08_VIII._Neural_Networks-_Representation_Week_4/03_Model_Representation_I_12_min.mp4 14.2 MB02_II._Linear_Regression_with_One_Variable_Week_1/05_Gradient_Descent_11_min.mp4 14.2 MB09_IX._Neural_Networks-_Learning_Week_5/05_Gradient_Checking_12_min.mp4 14.2 MB01_I._Introduction_Week_1/03_Supervised_Learning_12_min.mp4 14.1 MB08_VIII._Neural_Networks-_Representation_Week_4/04_Model_Representation_II_12_min.mp4 14.1 MB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min_jp2.zip 14.1 MB17_XVII._Large_Scale_Machine_Learning_Week_10/04_Stochastic_Gradient_Descent_Convergence_12_min.mp4 14.0 MB05_V._Octave_Tutorial_Week_2/04_Plotting_Data_10_min.mp4 14.0 MB11_XI._Machine_Learning_System_Design_Week_6/03_Error_Metrics_for_Skewed_Classes_12_min.mp4 13.9 MB06_VI._Logistic_Regression_Week_3/04_Cost_Function_11_min.mp4 13.7 MB02_II._Linear_Regression_with_One_Variable_Week_1/06_Gradient_Descent_Intuition_12_min.mp4 13.7 MB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.ogv 13.6 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/06_Learning_Curves_12_min.mp4 13.5 MB11_XI._Machine_Learning_System_Design_Week_6/05_Data_For_Machine_Learning_11_min.mp4 13.5 MB03_III._Linear_Algebra_Review_Week_1_Optional/06_Inverse_and_Transpose_11_min.mp4 13.5 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/05_Regularization_and_Bias-Variance_11_min.mp4 13.2 MB03_III._Linear_Algebra_Review_Week_1_Optional/04_Matrix_Matrix_Multiplication_11_min.mp4 13.2 MB02_II._Linear_Regression_with_One_Variable_Week_1/03_Cost_Function_-_Intuition_I_11_min.mp4 12.8 MB02_II._Linear_Regression_with_One_Variable_Week_1/07_Gradient_Descent_For_Linear_Regression_10_min.mp4 12.8 MB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min_jp2.zip 12.7 MB07_VII._Regularization_Week_3/03_Regularized_Linear_Regression_11_min.mp4 12.6 MB06_VI._Logistic_Regression_Week_3/05_Simplified_Cost_Function_and_Gradient_Descent_10_min.mp4 12.5 MB01_I._Introduction_Week_1/01_Welcome_7_min.mp4 12.5 MB14_XIV._Dimensionality_Reduction_Week_8/05_Choosing_the_Number_of_Principal_Components_11_min.mp4 12.4 MB12_XII._Support_Vector_Machines_Week_7/02_Large_Margin_Intuition_11_min.mp4 12.4 MB16_XVI._Recommender_Systems_Week_9/03_Collaborative_Filtering_10_min.mp4 12.3 MB15_XV._Anomaly_Detection_Week_9/02_Gaussian_Distribution_10_min.mp4 12.3 MB07_VII._Regularization_Week_3/02_Cost_Function_10_min.mp4 12.2 MB02_II._Linear_Regression_with_One_Variable_Week_1/04_Cost_Function_-_Intuition_II_9_min.mp4 11.9 MB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min_jp2.zip 11.8 MB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.mp4 11.7 MB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.mp4 11.7 MB07_VII._Regularization_Week_3/04_Regularized_Logistic_Regression_9_min.mp4 11.4 MB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.mp4 11.4 MB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.mp4 11.2 MB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min_jp2.zip 11.0 MB14_XIV._Dimensionality_Reduction_Week_8/03_Principal_Component_Analysis_Problem_Formulation_9_min.mp4 11.0 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min_jp2.zip 10.9 MB16_XVI._Recommender_Systems_Week_9/04_Collaborative_Filtering_Algorithm_9_min.mp4 10.8 MB14_XIV._Dimensionality_Reduction_Week_8/06_Reconstruction_from_Compressed_Representation_4_min.ogv 10.8 MB06_VI._Logistic_Regression_Week_3/01_Classification_8_min_jp2.zip 10.6 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min_jp2.zip 10.4 MB08_VIII._Neural_Networks-_Representation_Week_4/02_Neurons_and_the_Brain_8_min.mp4 10.4 MB03_III._Linear_Algebra_Review_Week_1_Optional/05_Matrix_Multiplication_Properties_9_min.mp4 10.3 MB16_XVI._Recommender_Systems_Week_9/06_Implementational_Detail-_Mean_Normalization_9_min.mp4 10.2 MB16_XVI._Recommender_Systems_Week_9/05_Vectorization-_Low_Rank_Matrix_Factorization_8_min.mp4 10.2 MB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min_jp2.zip 10.0 MB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.mp4 10.0 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/03_Gradient_Descent_in_Practice_I_-_Feature_Scaling_9_min.mp4 9.9 MB13_XIII._Clustering_Week_8/05_Choosing_the_Number_of_Clusters_8_min.mp4 9.9 MB09_IX._Neural_Networks-_Learning_Week_5/04_Implementation_Note-_Unrolling_Parameters_8_min.mp4 9.8 MB01_I._Introduction_Week_1/02_What_is_Machine_Learning_7_min.mp4 9.8 MB15_XV._Anomaly_Detection_Week_9/05_Anomaly_Detection_vs._Supervised_Learning_8_min.mp4 9.7 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/04_Gradient_Descent_in_Practice_II_-_Learning_Rate_9_min.mp4 9.7 MB02_II._Linear_Regression_with_One_Variable_Week_1/02_Cost_Function_8_min.mp4 9.5 MB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.mp4 9.4 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/04_Diagnosing_Bias_vs._Variance_8_min.mp4 9.4 MB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.ogv 9.3 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.mp4 9.3 MB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.mp4 9.2 MB13_XIII._Clustering_Week_8/04_Random_Initialization_8_min.mp4 9.1 MB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min_jp2.zip 8.9 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/02_Evaluating_a_Hypothesis_8_min.mp4 8.9 MB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.mp4 8.8 MB06_VI._Logistic_Regression_Week_3/02_Hypothesis_Representation_7_min.mp4 8.7 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/05_Features_and_Polynomial_Regression_8_min.mp4 8.7 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/07_Deciding_What_to_Do_Next_Revisited_7_min.mp4 8.6 MB13_XIII._Clustering_Week_8/03_Optimization_Objective_7_min.mp4 8.5 MB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min_jp2.zip 8.5 MB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.mp4 8.3 MB08_VIII._Neural_Networks-_Representation_Week_4/05_Examples_and_Intuitions_I_7_min.mp4 8.3 MB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.mp4 8.0 MB09_IX._Neural_Networks-_Learning_Week_5/06_Random_Initialization_7_min.mp4 7.9 MB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min_jp2.zip 7.9 MB03_III._Linear_Algebra_Review_Week_1_Optional/02_Addition_and_Scalar_Multiplication_7_min.mp4 7.8 MB17_XVII._Large_Scale_Machine_Learning_Week_10/03_Mini-Batch_Gradient_Descent_6_min.mp4 7.7 MB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min_jp2.zip 7.5 MB06_VI._Logistic_Regression_Week_3/07_Multiclass_Classification-_One-vs-all_6_min.mp4 7.3 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.mp4 7.2 MB01_I._Introduction_Week_1/01_Welcome_7_min_jp2.zip 7.0 MB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min_jp2.zip 6.9 MB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.mp4 6.8 MB14_XIV._Dimensionality_Reduction_Week_8/02_Motivation_II-_Visualization_6_min.mp4 6.6 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/07_Normal_Equation_Noninvertibility_Optional_6_min.mp4 6.5 MB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.pptx 6.4 MB19_XIX._Conclusion/01_Summary_and_Thank_You_5_min.mp4 6.4 MB02_II._Linear_Regression_with_One_Variable_Week_1/08_Whats_Next_6_min.mp4 6.4 MB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min_jp2.zip 6.4 MB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.pptx 6.3 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/02_Gradient_Descent_for_Multiple_Variables_5_min.mp4 6.1 MB05_V._Octave_Tutorial_Week_2/07_Working_on_and_Submitting_Programming_Exercises_4_min.mp4 5.7 MB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.pptx 5.6 MB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.pptx 5.6 MB14_XIV._Dimensionality_Reduction_Week_8/06_Reconstruction_from_Compressed_Representation_4_min.mp4 5.2 MB
08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.pdf 5.2 MB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.pptx 5.2 MB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.pptx 5.2 MB08_VIII._Neural_Networks-_Representation_Week_4/07_Multiclass_Classification_4_min.mp4 5.1 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.pptx 4.6 MB01_I._Introduction_Week_1/01_Welcome_7_min.pptx 4.2 MB.____padding_file/1 4.2 MB.____padding_file/5 4.2 MB.____padding_file/425 4.2 MB.____padding_file/452 4.2 MB.____padding_file/428 4.2 MB.____padding_file/326 4.2 MB.____padding_file/134 4.2 MB.____padding_file/580 4.2 MB.____padding_file/328 4.2 MB.____padding_file/362 4.2 MB.____padding_file/451 4.2 MB.____padding_file/487 4.2 MB.____padding_file/243 4.2 MB.____padding_file/460 4.2 MB.____padding_file/305 4.2 MB.____padding_file/564 4.2 MB.____padding_file/282 4.2 MB.____padding_file/51 4.2 MB.____padding_file/467 4.2 MB.____padding_file/533 4.2 MB.____padding_file/64 4.2 MB.____padding_file/126 4.2 MB.____padding_file/382 4.2 MB.____padding_file/355 4.2 MB.____padding_file/173 4.2 MB.____padding_file/53 4.2 MB.____padding_file/493 4.2 MB.____padding_file/417 4.2 MB.____padding_file/390 4.2 MB.____padding_file/210 4.2 MB.____padding_file/557 4.2 MB.____padding_file/530 4.2 MB.____padding_file/502 4.2 MB.____padding_file/339 4.2 MB.____padding_file/181 4.2 MB.____padding_file/353 4.2 MB.____padding_file/397 4.2 MB.____padding_file/107 4.2 MB.____padding_file/251 4.2 MB.____padding_file/361 4.2 MB.____padding_file/184 4.2 MB.____padding_file/149 4.2 MB.____padding_file/82 4.2 MB.____padding_file/522 4.2 MB.____padding_file/140 4.2 MB.____padding_file/227 4.2 MB.____padding_file/303 4.2 MB.____padding_file/235 4.2 MB.____padding_file/91 4.2 MB.____padding_file/325 4.2 MB.____padding_file/458 4.2 MB.____padding_file/56 4.2 MB.____padding_file/285 4.2 MB.____padding_file/374 4.2 MB.____padding_file/479 4.2 MB.____padding_file/133 4.2 MB.____padding_file/12 4.2 MB.____padding_file/463 4.2 MB.____padding_file/579 4.2 MB.____padding_file/142 4.2 MB.____padding_file/200 4.2 MB.____padding_file/495 4.2 MB.____padding_file/204 4.2 MB.____padding_file/130 4.2 MB.____padding_file/388 4.2 MB.____padding_file/114 4.2 MB.____padding_file/157 4.2 MB.____padding_file/196 4.2 MB.____padding_file/84 4.2 MB.____padding_file/440 4.2 MB.____padding_file/510 4.2 MB.____padding_file/366 4.2 MB.____padding_file/63 4.2 MB.____padding_file/343 4.2 MB.____padding_file/33 4.2 MB.____padding_file/50 4.2 MB.____padding_file/179 4.2 MB.____padding_file/212 4.2 MB.____padding_file/297 4.2 MB.____padding_file/486 4.2 MB.____padding_file/153 4.2 MB.____padding_file/347 4.2 MB.____padding_file/14 4.2 MB.____padding_file/172 4.2 MB.____padding_file/370 4.2 MB.____padding_file/0 4.2 MB.____padding_file/568 4.2 MB.____padding_file/308 4.2 MB.____padding_file/331 4.2 MB.____padding_file/105 4.2 MB.____padding_file/169 4.2 MB.____padding_file/498 4.2 MB.____padding_file/560 4.2 MB.____padding_file/475 4.2 MB.____padding_file/409 4.2 MB.____padding_file/528 4.2 MB.____padding_file/289 4.2 MB.____padding_file/555 4.2 MB.____padding_file/280 4.2 MB.____padding_file/254 4.2 MB.____padding_file/358 4.2 MB.____padding_file/393 4.2 MB.____padding_file/483 4.2 MB.____padding_file/192 4.2 MB.____padding_file/293 4.2 MB.____padding_file/576 4.2 MB.____padding_file/381 4.2 MB.____padding_file/118 4.2 MB.____padding_file/21 4.2 MB.____padding_file/242 4.2 MB.____padding_file/148 4.2 MB.____padding_file/81 4.2 MB.____padding_file/215 4.2 MB.____padding_file/139 4.2 MB.____padding_file/258 4.2 MB.____padding_file/405 4.2 MB.____padding_file/90 4.2 MB.____padding_file/122 4.2 MB.____padding_file/563 4.2 MB.____padding_file/541 4.2 MB.____padding_file/514 4.2 MB.____padding_file/161 4.2 MB.____padding_file/219 4.2 MB.____padding_file/444 4.2 MB.____padding_file/25 4.2 MB.____padding_file/165 4.2 MB.____padding_file/549 4.2 MB.____padding_file/471 4.2 MB.____padding_file/17 4.2 MB.____padding_file/436 4.2 MB.____padding_file/156 4.2 MB.____padding_file/506 4.2 MB.____padding_file/223 4.2 MB.____padding_file/231 4.2 MB.____padding_file/448 4.2 MB.____padding_file/501 4.2 MB.____padding_file/95 4.2 MB.____padding_file/423 4.2 MB.____padding_file/68 4.2 MB.____padding_file/87 4.2 MB.____padding_file/518 4.2 MB.____padding_file/37 4.2 MB.____padding_file/466 4.2 MB.____padding_file/4 4.2 MB.____padding_file/335 4.2 MB.____padding_file/401 4.2 MB.____padding_file/152 4.2 MB.____padding_file/584 4.2 MB.____padding_file/41 4.2 MB.____padding_file/492 4.2 MB.____padding_file/110 4.2 MB.____padding_file/416 4.2 MB.____padding_file/72 4.2 MB.____padding_file/60 4.2 MB.____padding_file/572 4.2 MB.____padding_file/432 4.2 MB.____padding_file/45 4.2 MB.____padding_file/29 4.2 MB.____padding_file/188 4.2 MB.____padding_file/537 4.2 MB.____padding_file/125 4.2 MB.____padding_file/239 4.2 MB.____padding_file/209 4.2 MB.____padding_file/266 4.2 MB.____padding_file/545 4.2 MB.____padding_file/76 4.2 MB.____padding_file/413 4.2 MB.____padding_file/249 4.2 MB.____padding_file/338 4.2 MB.____padding_file/99 4.2 MB.____padding_file/234 4.2 MB.____padding_file/521 4.2 MB.____padding_file/396 4.2 MB.____padding_file/270 4.2 MB.____padding_file/352 4.2 MB.____padding_file/145 4.2 MB.____padding_file/312 4.2 MB.____padding_file/320 4.2 MB.____padding_file/302 4.2 MB.____padding_file/378 4.2 MB.____padding_file/226 4.2 MB.____padding_file/160 4.2 MB.____padding_file/164 4.2 MB.____padding_file/457 4.2 MB.____padding_file/373 4.2 MB.____padding_file/11 4.2 MB.____padding_file/509 4.2 MB.____padding_file/67 4.2 MB.____padding_file/387 4.2 MB.____padding_file/342 4.2 MB.____padding_file/199 4.2 MB.____padding_file/316 4.2 MB.____padding_file/262 4.2 MB.____padding_file/113 4.2 MB.____padding_file/32 4.2 MB.____padding_file/195 4.2 MB.____padding_file/203 4.2 MB.____padding_file/478 4.2 MB.____padding_file/178 4.2 MB.____padding_file/94 4.2 MB.____padding_file/365 4.2 MB.____padding_file/129 4.2 MB.____padding_file/296 4.2 MB.____padding_file/439 4.2 MB.____padding_file/346 4.2 MB.____padding_file/59 4.2 MB.____padding_file/567 4.2 MB.____padding_file/369 4.2 MB.____padding_file/168 4.2 MB.____padding_file/104 4.2 MB.____padding_file/279 4.2 MB.____padding_file/408 4.2 MB.____padding_file/527 4.2 MB.____padding_file/288 4.2 MB.____padding_file/554 4.2 MB.____padding_file/191 4.2 MB.____padding_file/292 4.2 MB.____padding_file/474 4.2 MB.____padding_file/20 4.2 MB.____padding_file/274 4.2 MB.____padding_file/80 4.2 MB.____padding_file/482 4.2 MB.____padding_file/575 4.2 MB.____padding_file/257 4.2 MB.____padding_file/117 4.2 MB.____padding_file/540 4.2 MB.____padding_file/404 4.2 MB.____padding_file/121 4.2 MB.____padding_file/513 4.2 MB.____padding_file/218 4.2 MB.____padding_file/548 4.2 MB.____padding_file/443 4.2 MB.____padding_file/24 4.2 MB.____padding_file/230 4.2 MB.____padding_file/470 4.2 MB.____padding_file/424 4.2 MB.____padding_file/505 4.2 MB.____padding_file/517 4.2 MB.____padding_file/435 4.2 MB.____padding_file/222 4.2 MB.____padding_file/36 4.2 MB.____padding_file/447 4.2 MB.____padding_file/422 4.2 MB.____padding_file/334 4.2 MB.____padding_file/44 4.2 MB.____padding_file/583 4.2 MB.____padding_file/400 4.2 MB.____padding_file/28 4.2 MB.____padding_file/40 4.2 MB.____padding_file/536 4.2 MB.____padding_file/71 4.2 MB.____padding_file/238 4.2 MB.____padding_file/412 4.2 MB.____padding_file/187 4.2 MB.____padding_file/571 4.2 MB.____padding_file/544 4.2 MB.____padding_file/431 4.2 MB.____padding_file/75 4.2 MB.____padding_file/98 4.2 MB.____padding_file/265 4.2 MB.____padding_file/248 4.2 MB.____padding_file/319 4.2 MB.____padding_file/269 4.2 MB.____padding_file/377 4.2 MB.____padding_file/311 4.2 MB.____padding_file/315 4.2 MB.____padding_file/261 4.2 MB.____padding_file/273 4.1 MB.____padding_file/426 4.1 MB.____padding_file/3 4.1 MB.____padding_file/73 4.1 MB.____padding_file/2 4.1 MB.____padding_file/327 4.1 MB.____padding_file/445 4.1 MB.____padding_file/304 4.1 MB.____padding_file/317 4.1 MB.____padding_file/183 4.1 MB.____padding_file/101 4.1 MB.____padding_file/529 4.1 MB.____padding_file/459 4.1 MB.____padding_file/83 4.1 MB.____padding_file/281 4.1 MB.____padding_file/556 4.1 MB.____padding_file/52 4.1 MB.____padding_file/109 4.1 MB.____padding_file/329 4.1 MB.____padding_file/106 4.0 MB.____padding_file/531 4.0 MB.____padding_file/180 4.0 MB.____padding_file/336 4.0 MB.____padding_file/354 4.0 MB.____padding_file/250 4.0 MB.____padding_file/389 4.0 MB.____padding_file/306 4.0 MB.____padding_file/85 4.0 MB.____padding_file/494 4.0 MB.____padding_file/473 4.0 MB.____padding_file/141 4.0 MB.____padding_file/54 4.0 MB.____padding_file/211 4.0 MB.____padding_file/166 4.0 MB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.pptx 4.0 MB.____padding_file/23 4.0 MB.____padding_file/519 4.0 MB.____padding_file/13 4.0 MB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.mp4 4.0 MB.____padding_file/558 4.0 MB.____padding_file/283 4.0 MB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.pptx 4.0 MB.____padding_file/356 4.0 MB.____padding_file/461 4.0 MB.____padding_file/391 4.0 MB.____padding_file/182 4.0 MB.____padding_file/420 3.9 MB.____padding_file/108 3.9 MB.____padding_file/496 3.9 MB.____padding_file/150 3.9 MB.____padding_file/213 3.9 MB.____padding_file/252 3.9 MB.____padding_file/371 3.9 MB.____padding_file/116 3.9 MB.____padding_file/512 3.9 MB.____padding_file/446 3.9 MB.____padding_file/236 3.9 MB.____padding_file/500 3.9 MB.____padding_file/143 3.9 MB.____padding_file/15 3.8 MB.____padding_file/394 3.8 MB.____padding_file/42 3.8 MB.____padding_file/7 3.8 MB.____padding_file/103 3.8 MB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.pptx 3.8 MB.____padding_file/310 3.8 MB.____padding_file/351 3.8 MB.____padding_file/421 3.8 MB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.pptx 3.8 MB.____padding_file/499 3.7 MB.____padding_file/525 3.7 MB.____padding_file/441 3.7 MB.____padding_file/256 3.7 MB.____padding_file/237 3.7 MB.____padding_file/309 3.6 MB.____padding_file/462 3.6 MB.____padding_file/299 3.6 MB.____padding_file/419 3.6 MB.____padding_file/472 3.6 MB.____padding_file/511 3.6 MB.____padding_file/516 3.6 MB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.pdf 3.5 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.pptx 3.5 MB.____padding_file/244 3.5 MB.____padding_file/96 3.5 MB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.pdf 3.5 MB.____padding_file/340 3.5 MB01_I._Introduction_Week_1/01_Welcome_7_min.pdf 3.5 MB.____padding_file/398 3.4 MB.____padding_file/429 3.4 MB.____padding_file/383 3.4 MB.____padding_file/268 3.4 MB.____padding_file/131 3.3 MB.____padding_file/348 3.3 MB.____padding_file/89 3.3 MB.____padding_file/225 3.3 MB.____padding_file/480 3.3 MB.____padding_file/546 3.3 MB.____padding_file/186 3.3 MB.____padding_file/322 3.3 MB.____padding_file/515 3.2 MB.____padding_file/456 3.2 MB.____padding_file/185 3.2 MB.____padding_file/47 3.2 MB.____padding_file/27 3.2 MB.____padding_file/208 3.2 MB.____padding_file/507 3.2 MB.____padding_file/102 3.2 MB.____padding_file/577 3.2 MB.____padding_file/349 3.2 MB.____padding_file/135 3.2 MB.____padding_file/570 3.1 MB.____padding_file/314 3.1 MB.____padding_file/162 3.1 MB.____padding_file/543 3.1 MB.____padding_file/407 3.1 MB.____padding_file/146 3.1 MB.____padding_file/206 3.1 MB.____padding_file/402 3.1 MB.____padding_file/566 3.0 MB.____padding_file/291 3.0 MB.____padding_file/245 3.0 MB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.pdf 3.0 MB.____padding_file/375 3.0 MB.____padding_file/372 2.9 MB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.pptx 2.9 MB.____padding_file/538 2.9 MB.____padding_file/454 2.9 MB.____padding_file/367 2.9 MB.____padding_file/30 2.9 MB.____padding_file/241 2.8 MB.____padding_file/6 2.8 MB.____padding_file/66 2.8 MB.____padding_file/437 2.8 MB.____padding_file/65 2.8 MB.____padding_file/477 2.8 MB.____padding_file/88 2.8 MB.____padding_file/138 2.8 MB.____padding_file/434 2.8 MB.____padding_file/224 2.7 MB.____padding_file/247 2.7 MB.____padding_file/344 2.7 MB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.pptx 2.7 MB.____padding_file/176 2.7 MB.____padding_file/214 2.7 MB.____padding_file/399 2.7 MB.____padding_file/395 2.7 MB.____padding_file/267 2.7 MB.____padding_file/119 2.7 MB.____padding_file/92 2.7 MB.____padding_file/363 2.7 MB.____padding_file/449 2.7 MB.____padding_file/112 2.6 MB.____padding_file/490 2.6 MB.____padding_file/228 2.6 MB.____padding_file/158 2.6 MB.____padding_file/115 2.6 MB.____padding_file/453 2.6 MB.____padding_file/263 2.5 MB.____padding_file/55 2.5 MB.____padding_file/403 2.5 MB.____padding_file/552 2.5 MB.____padding_file/272 2.5 MB.____padding_file/427 2.5 MB.____padding_file/155 2.5 MB.____padding_file/380 2.5 MB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.pdf 2.5 MB.____padding_file/430 2.5 MB.____padding_file/197 2.4 MB.____padding_file/147 2.4 MB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.pdf 2.4 MB.____padding_file/350 2.4 MB.____padding_file/201 2.4 MB.____padding_file/418 2.4 MB.____padding_file/62 2.4 MB.____padding_file/520 2.4 MB.____padding_file/359 2.3 MB.____padding_file/569 2.3 MB.____padding_file/124 2.3 MB.____padding_file/455 2.3 MB.____padding_file/332 2.3 MB.____padding_file/476 2.3 MB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.pdf 2.3 MB.____padding_file/259 2.3 MB.____padding_file/35 2.3 MB.____padding_file/19 2.2 MB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.pdf 2.2 MB.____padding_file/111 2.2 MB.____padding_file/574 2.2 MB.____padding_file/526 2.2 MB.____padding_file/216 2.2 MB.____padding_file/163 2.2 MB.____padding_file/357 2.2 MB.____padding_file/22 2.1 MB.____padding_file/300 2.1 MB.____padding_file/48 2.1 MB.____padding_file/127 2.1 MB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.pdf 2.1 MB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.pdf 2.1 MB.____padding_file/43 2.1 MB.____padding_file/10 2.0 MB.____padding_file/503 2.0 MB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.pptx 2.0 MB.____padding_file/392 2.0 MB.____padding_file/330 2.0 MB.____padding_file/170 2.0 MB.____padding_file/484 2.0 MB.____padding_file/438 2.0 MB.____padding_file/128 2.0 MB.____padding_file/34 2.0 MB.____padding_file/385 2.0 MB.____padding_file/301 2.0 MB.____padding_file/410 1.9 MB.____padding_file/323 1.9 MB.____padding_file/264 1.9 MB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.pdf 1.9 MB.____padding_file/132 1.9 MB.____padding_file/379 1.8 MB.____padding_file/578 1.8 MB.____padding_file/151 1.8 MB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.pdf 1.8 MB.____padding_file/489 1.8 MB.____padding_file/561 1.8 MB.____padding_file/246 1.8 MB.____padding_file/193 1.8 MB.____padding_file/550 1.8 MB.____padding_file/93 1.7 MB.____padding_file/277 1.7 MB.____padding_file/221 1.7 MB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min_jp2.zip 1.7 MB.____padding_file/295 1.7 MB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.pdf 1.7 MB.____padding_file/497 1.6 MB.____padding_file/565 1.6 MB.____padding_file/415 1.6 MB.____padding_file/120 1.6 MB.____padding_file/333 1.6 MB.____padding_file/559 1.6 MB.____padding_file/46 1.6 MB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.pdf 1.6 MB.____padding_file/144 1.6 MB.____padding_file/508 1.5 MB.____padding_file/260 1.5 MB.____padding_file/284 1.5 MB.____padding_file/31 1.5 MB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.pdf 1.5 MB.____padding_file/278 1.5 MB.____padding_file/345 1.5 MB.____padding_file/74 1.5 MB.____padding_file/481 1.4 MB.____padding_file/174 1.4 MB
entered_login.html 1.4 MB.____padding_file/86 1.4 MB.____padding_file/581 1.4 MB.____padding_file/485 1.4 MB.____padding_file/202 1.3 MB.____padding_file/324 1.3 MB.____padding_file/313 1.2 MB.____padding_file/488 1.2 MB.____padding_file/159 1.2 MB.____padding_file/137 1.2 MB.____padding_file/240 1.2 MB.____padding_file/100 1.2 MB.____padding_file/318 1.2 MB.____padding_file/294 1.2 MB.____padding_file/287 1.2 MB.____padding_file/364 1.1 MB.____padding_file/167 1.1 MB.____padding_file/69 1.1 MB.____padding_file/198 1.1 MB.____padding_file/414 1.1 MB.____padding_file/450 1.1 MB.____padding_file/8 1.1 MB.____padding_file/469 1.1 MB.____padding_file/535 1.1 MB.____padding_file/582 1.1 MB.____padding_file/468 1.0 MB.____padding_file/337 1.0 MB.____padding_file/341 981.1 kB.____padding_file/360 976.7 kB.____padding_file/194 970.6 kB.____padding_file/275 891.4 kB.____padding_file/26 886.4 kB.____padding_file/532 886.0 kB.____padding_file/523 873.9 kB.____padding_file/190 871.8 kB.____padding_file/276 831.2 kB.____padding_file/411 822.2 kB.____padding_file/253 814.8 kB.____padding_file/78 803.5 kB.____padding_file/433 785.8 kB.____padding_file/539 773.2 kB.____padding_file/551 756.6 kB.____padding_file/79 732.5 kB.____padding_file/217 722.5 kB.____padding_file/61 718.0 kB.____padding_file/9 705.9 kB.____padding_file/57 698.5 kB.____padding_file/491 677.1 kB.____padding_file/233 669.9 kB.____padding_file/154 668.5 kB.____padding_file/504 666.1 kB.____padding_file/207 661.0 kB.____padding_file/534 602.4 kB.____padding_file/562 595.8 kB.____padding_file/220 582.9 kB.____padding_file/464 564.4 kB.____padding_file/465 538.3 kB.____padding_file/307 526.0 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.pdf 509.6 kB.____padding_file/442 502.4 kB.____padding_file/232 456.5 kB.____padding_file/376 423.8 kB.____padding_file/177 422.1 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.pptx 417.1 kB.____padding_file/553 393.5 kB.____padding_file/286 388.2 kB.____padding_file/97 386.2 kB.____padding_file/384 375.0 kB.____padding_file/547 364.2 kB.____padding_file/205 355.4 kB.____padding_file/524 348.0 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min_djvu.xml 344.9 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min_djvu.xml 338.1 kB.____padding_file/18 324.3 kB.____padding_file/136 292.7 kB.____padding_file/70 284.0 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min_djvu.xml 268.3 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min_djvu.xml 266.2 kB.____padding_file/189 260.8 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min_djvu.xml 255.1 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min_djvu.xml 252.6 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.pdf 248.2 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min_djvu.xml 241.7 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min_djvu.xml 237.5 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min_djvu.xml 237.2 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min_djvu.xml 236.5 kB.____padding_file/49 230.0 kB.____padding_file/39 224.2 kB.____padding_file/16 219.2 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min_djvu.xml 218.8 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min_djvu.xml 211.4 kB.____padding_file/321 206.6 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min_abbyy.gz 199.8 kB.____padding_file/255 198.2 kB.____padding_file/386 188.7 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min_abbyy.gz 185.3 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min_djvu.xml 183.5 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min_abbyy.gz 173.5 kB.____padding_file/573 171.8 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min_abbyy.gz 170.0 kB01_I._Introduction_Week_1/01_Welcome_7_min_djvu.xml 169.3 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min_djvu.xml 167.9 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min_abbyy.gz 160.5 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min_abbyy.gz 159.5 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min_abbyy.gz 152.9 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min_abbyy.gz 150.2 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min_djvu.xml 149.4 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min_abbyy.gz 146.5 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min_djvu.xml 142.4 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min_abbyy.gz 135.1 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min_abbyy.gz 134.2 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min_abbyy.gz 131.5 kB01_I._Introduction_Week_1/01_Welcome_7_min_abbyy.gz 130.8 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min_abbyy.gz 130.1 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min_abbyy.gz 123.3 kB.____padding_file/368 116.8 kB.____padding_file/123 111.4 kB.____padding_file/58 109.2 kB.____padding_file/175 104.1 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min_abbyy.gz 101.7 kB.____padding_file/298 90.6 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min_abbyy.gz 78.3 kBacademictorrents_e8b1f9c5bf555fe58bc73addb83457dd6da69630_academictorrents.torrent 72.4 kB.____padding_file/38 69.3 kB.____padding_file/229 64.2 kB
academictorrents_e8b1f9c5bf555fe58bc73addb83457dd6da69630_academictorrents_torrent.txt 63.7 kB.____padding_file/271 51.5 kB.____padding_file/77 51.4 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min_djvu.xml 50.1 kB12_XII._Support_Vector_Machines_Week_7/06_Using_An_SVM_21_min.srt 44.5 kB.____padding_file/406 44.1 kB12_XII._Support_Vector_Machines_Week_7/03_Mathematics_Behind_Large_Margin_Classification_Optional_20_min.srt 36.7 kB18_XVIII._Application_Example-_Photo_OCR/03_Getting_Lots_of_Data_and_Artificial_Data_16_min.srt 36.0 kB18_XVIII._Application_Example-_Photo_OCR/02_Sliding_Windows_15_min.srt 32.2 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/06_Normal_Equation_16_min.srt 31.9 kB12_XII._Support_Vector_Machines_Week_7/05_Kernels_II_16_min.srt 31.4 kB18_XVIII._Application_Example-_Photo_OCR/04_Ceiling_Analysis-_What_Part_of_the_Pipeline_to_Work_on_Next_14_min.srt 31.2 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.srt 30.1 kB12_XII._Support_Vector_Machines_Week_7/04_Kernels_I_16_min.srt 29.8 kB01_I._Introduction_Week_1/04_Unsupervised_Learning_14_min.srt 29.8 kB17_XVII._Large_Scale_Machine_Learning_Week_10/06_Map_Reduce_and_Data_Parallelism_14_min.srt 29.6 kB05_V._Octave_Tutorial_Week_2/02_Moving_Data_Around_16_min.srt 29.3 kB11_XI._Machine_Learning_System_Design_Week_6/04_Trading_Off_Precision_and_Recall_14_min.srt 29.3 kB14_XIV._Dimensionality_Reduction_Week_8/04_Principal_Component_Analysis_Algorithm_15_min.srt 29.3 kB16_XVI._Recommender_Systems_Week_9/02_Content_Based_Recommendations_15_min.srt 29.3 kB06_VI._Logistic_Regression_Week_3/06_Advanced_Optimization_14_min.srt 28.5 kB09_IX._Neural_Networks-_Learning_Week_5/07_Putting_It_Together_14_min.srt 28.3 kB17_XVII._Large_Scale_Machine_Learning_Week_10/05_Online_Learning_13_min.srt 28.3 kB11_XI._Machine_Learning_System_Design_Week_6/02_Error_Analysis_13_min.srt 28.1 kB15_XV._Anomaly_Detection_Week_9/07_Multivariate_Gaussian_Distribution_Optional_14_min.srt 28.1 kB15_XV._Anomaly_Detection_Week_9/04_Developing_and_Evaluating_an_Anomaly_Detection_System_13_min.srt 27.9 kB06_VI._Logistic_Regression_Week_3/03_Decision_Boundary_15_min.srt 27.4 kB14_XIV._Dimensionality_Reduction_Week_8/07_Advice_for_Applying_PCA_13_min.srt 27.0 kB15_XV._Anomaly_Detection_Week_9/08_Anomaly_Detection_using_the_Multivariate_Gaussian_Distribution_Optional_14_min.srt 26.9 kB13_XIII._Clustering_Week_8/02_K-Means_Algorithm_13_min.srt 26.9 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.srt 26.0 kB05_V._Octave_Tutorial_Week_2/06_Vectorization_14_min.srt 25.8 kB15_XV._Anomaly_Detection_Week_9/06_Choosing_What_Features_to_Use_12_min.srt 25.7 kB09_IX._Neural_Networks-_Learning_Week_5/03_Backpropagation_Intuition_13_min.srt 25.6 kB05_V._Octave_Tutorial_Week_2/03_Computing_on_Data_13_min.srt 25.5 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/06_Learning_Curves_12_min.srt 25.3 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/03_Model_Selection_and_Train-Validation-Test_Sets_12_min.srt 25.2 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min_abbyy.gz 25.0 kB03_III._Linear_Algebra_Review_Week_1_Optional/03_Matrix_Vector_Multiplication_14_min.srt 24.8 kB09_IX._Neural_Networks-_Learning_Week_5/05_Gradient_Checking_12_min.srt 24.1 kB15_XV._Anomaly_Detection_Week_9/03_Algorithm_12_min.srt 24.1 kB05_V._Octave_Tutorial_Week_2/05_Control_Statements-_for_while_if_statements_13_min.srt 23.9 kB11_XI._Machine_Learning_System_Design_Week_6/05_Data_For_Machine_Learning_11_min.srt 23.7 kB09_IX._Neural_Networks-_Learning_Week_5/02_Backpropagation_Algorithm_12_min.srt 23.4 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/05_Regularization_and_Bias-Variance_11_min.srt 23.1 kB08_VIII._Neural_Networks-_Representation_Week_4/04_Model_Representation_II_12_min.srt 23.0 kB06_VI._Logistic_Regression_Week_3/04_Cost_Function_11_min.srt 22.7 kB11_XI._Machine_Learning_System_Design_Week_6/03_Error_Metrics_for_Skewed_Classes_12_min.srt 22.6 kB08_VIII._Neural_Networks-_Representation_Week_4/03_Model_Representation_I_12_min.srt 22.1 kB12_XII._Support_Vector_Machines_Week_7/02_Large_Margin_Intuition_11_min.srt 21.8 kB14_XIV._Dimensionality_Reduction_Week_8/05_Choosing_the_Number_of_Principal_Components_11_min.srt 21.7 kB03_III._Linear_Algebra_Review_Week_1_Optional/06_Inverse_and_Transpose_11_min.srt 21.6 kB12_XII._Support_Vector_Machines_Week_7/06_Using_An_SVM_21_min.txt 21.2 kB15_XV._Anomaly_Detection_Week_9/02_Gaussian_Distribution_10_min.srt 21.1 kB03_III._Linear_Algebra_Review_Week_1_Optional/04_Matrix_Matrix_Multiplication_11_min.srt 21.1 kB07_VII._Regularization_Week_3/03_Regularized_Linear_Regression_11_min.srt 20.9 kB16_XVI._Recommender_Systems_Week_9/03_Collaborative_Filtering_10_min.srt 20.7 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.srt 20.6 kB07_VII._Regularization_Week_3/02_Cost_Function_10_min.srt 20.2 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.srt 20.1 kB06_VI._Logistic_Regression_Week_3/05_Simplified_Cost_Function_and_Gradient_Descent_10_min.srt 20.0 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.srt 19.7 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.srt 19.5 kB02_II._Linear_Regression_with_One_Variable_Week_1/07_Gradient_Descent_For_Linear_Regression_10_min.srt 19.2 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/04_Gradient_Descent_in_Practice_II_-_Learning_Rate_9_min.srt 18.9 kB14_XIV._Dimensionality_Reduction_Week_8/03_Principal_Component_Analysis_Problem_Formulation_9_min.srt 18.9 kB17_XVII._Large_Scale_Machine_Learning_Week_10/02_Stochastic_Gradient_Descent_13_min.srt 18.6 kB13_XIII._Clustering_Week_8/05_Choosing_the_Number_of_Clusters_8_min.srt 18.4 kB05_V._Octave_Tutorial_Week_2/04_Plotting_Data_10_min.srt 17.8 kB07_VII._Regularization_Week_3/04_Regularized_Logistic_Regression_9_min.srt 17.6 kB08_VIII._Neural_Networks-_Representation_Week_4/06_Examples_and_Intuitions_II_10_min.srt 17.5 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/03_Gradient_Descent_in_Practice_I_-_Feature_Scaling_9_min.srt 17.4 kB01_I._Introduction_Week_1/03_Supervised_Learning_12_min.srt 17.2 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.srt 17.2 kB03_III._Linear_Algebra_Review_Week_1_Optional/05_Matrix_Multiplication_Properties_9_min.srt 17.2 kB16_XVI._Recommender_Systems_Week_9/06_Implementational_Detail-_Mean_Normalization_9_min.srt 17.0 kB16_XVI._Recommender_Systems_Week_9/04_Collaborative_Filtering_Algorithm_9_min.srt 16.9 kB15_XV._Anomaly_Detection_Week_9/05_Anomaly_Detection_vs._Supervised_Learning_8_min.srt 16.8 kB08_VIII._Neural_Networks-_Representation_Week_4/02_Neurons_and_the_Brain_8_min.srt 16.8 kB12_XII._Support_Vector_Machines_Week_7/03_Mathematics_Behind_Large_Margin_Classification_Optional_20_min.txt 16.8 kB18_XVIII._Application_Example-_Photo_OCR/03_Getting_Lots_of_Data_and_Artificial_Data_16_min.txt 16.8 kB16_XVI._Recommender_Systems_Week_9/05_Vectorization-_Low_Rank_Matrix_Factorization_8_min.srt 16.7 kB13_XIII._Clustering_Week_8/04_Random_Initialization_8_min.srt 16.6 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.srt 16.6 kB17_XVII._Large_Scale_Machine_Learning_Week_10/04_Stochastic_Gradient_Descent_Convergence_12_min.srt 16.5 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/04_Diagnosing_Bias_vs._Variance_8_min.srt 16.5 kB.____padding_file/171 16.4 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.srt 16.4 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/05_Features_and_Polynomial_Regression_8_min.srt 16.3 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.srt 16.3 kB02_II._Linear_Regression_with_One_Variable_Week_1/06_Gradient_Descent_Intuition_12_min.srt 15.9 kB02_II._Linear_Regression_with_One_Variable_Week_1/05_Gradient_Descent_11_min.srt 15.8 kB09_IX._Neural_Networks-_Learning_Week_5/04_Implementation_Note-_Unrolling_Parameters_8_min.srt 15.3 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/06_Normal_Equation_16_min.txt 15.1 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.srt 15.1 kB18_XVIII._Application_Example-_Photo_OCR/04_Ceiling_Analysis-_What_Part_of_the_Pipeline_to_Work_on_Next_14_min.txt 15.0 kB18_XVIII._Application_Example-_Photo_OCR/02_Sliding_Windows_15_min.txt 14.9 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min_scandata.xml 14.9 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.srt 14.9 kB12_XII._Support_Vector_Machines_Week_7/05_Kernels_II_16_min.txt 14.8 kB06_VI._Logistic_Regression_Week_3/02_Hypothesis_Representation_7_min.srt 14.5 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/07_Deciding_What_to_Do_Next_Revisited_7_min.srt 14.4 kB09_IX._Neural_Networks-_Learning_Week_5/06_Random_Initialization_7_min.srt 14.3 kB01_I._Introduction_Week_1/04_Unsupervised_Learning_14_min.txt 14.2 kB13_XIII._Clustering_Week_8/03_Optimization_Objective_7_min.srt 14.0 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min.txt 13.8 kB06_VI._Logistic_Regression_Week_3/06_Advanced_Optimization_14_min.txt 13.8 kB17_XVII._Large_Scale_Machine_Learning_Week_10/06_Map_Reduce_and_Data_Parallelism_14_min.txt 13.7 kB11_XI._Machine_Learning_System_Design_Week_6/04_Trading_Off_Precision_and_Recall_14_min.txt 13.5 kB12_XII._Support_Vector_Machines_Week_7/04_Kernels_I_16_min.txt 13.5 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.srt 13.5 kB09_IX._Neural_Networks-_Learning_Week_5/07_Putting_It_Together_14_min.txt 13.4 kB08_VIII._Neural_Networks-_Representation_Week_4/05_Examples_and_Intuitions_I_7_min.srt 13.4 kB11_XI._Machine_Learning_System_Design_Week_6/02_Error_Analysis_13_min.txt 13.3 kB16_XVI._Recommender_Systems_Week_9/02_Content_Based_Recommendations_15_min.txt 13.3 kB15_XV._Anomaly_Detection_Week_9/04_Developing_and_Evaluating_an_Anomaly_Detection_System_13_min.txt 13.2 kB15_XV._Anomaly_Detection_Week_9/08_Anomaly_Detection_using_the_Multivariate_Gaussian_Distribution_Optional_14_min.txt 13.2 kB05_V._Octave_Tutorial_Week_2/02_Moving_Data_Around_16_min.txt 13.2 kB14_XIV._Dimensionality_Reduction_Week_8/04_Principal_Component_Analysis_Algorithm_15_min.txt 13.1 kB17_XVII._Large_Scale_Machine_Learning_Week_10/02_Stochastic_Gradient_Descent_13_min.txt 13.1 kB17_XVII._Large_Scale_Machine_Learning_Week_10/05_Online_Learning_13_min.txt 13.1 kB06_VI._Logistic_Regression_Week_3/07_Multiclass_Classification-_One-vs-all_6_min.srt 12.9 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min_scandata.xml 12.8 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.srt 12.7 kB15_XV._Anomaly_Detection_Week_9/07_Multivariate_Gaussian_Distribution_Optional_14_min.txt 12.7 kB14_XIV._Dimensionality_Reduction_Week_8/07_Advice_for_Applying_PCA_13_min.txt 12.5 kB02_II._Linear_Regression_with_One_Variable_Week_1/03_Cost_Function_-_Intuition_I_11_min.srt 12.4 kB06_VI._Logistic_Regression_Week_3/03_Decision_Boundary_15_min.txt 12.4 kB13_XIII._Clustering_Week_8/02_K-Means_Algorithm_13_min.txt 12.3 kBacademictorrents_e8b1f9c5bf555fe58bc73addb83457dd6da69630_meta.sqlite 12.3 kB03_III._Linear_Algebra_Review_Week_1_Optional/02_Addition_and_Scalar_Multiplication_7_min.srt 12.3 kB15_XV._Anomaly_Detection_Week_9/06_Choosing_What_Features_to_Use_12_min.txt 12.0 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/06_Learning_Curves_12_min.txt 12.0 kB01_I._Introduction_Week_1/01_Welcome_7_min_scandata.xml 11.9 kB17_XVII._Large_Scale_Machine_Learning_Week_10/04_Stochastic_Gradient_Descent_Convergence_12_min.txt 11.9 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min.txt 11.9 kB01_I._Introduction_Week_1/03_Supervised_Learning_12_min.txt 11.8 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/02_Evaluating_a_Hypothesis_8_min.srt 11.8 kB05_V._Octave_Tutorial_Week_2/06_Vectorization_14_min.txt 11.7 kB09_IX._Neural_Networks-_Learning_Week_5/05_Gradient_Checking_12_min.txt 11.7 kB09_IX._Neural_Networks-_Learning_Week_5/03_Backpropagation_Intuition_13_min.txt 11.6 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/03_Model_Selection_and_Train-Validation-Test_Sets_12_min.txt 11.5 kB02_II._Linear_Regression_with_One_Variable_Week_1/04_Cost_Function_-_Intuition_II_9_min.srt 11.4 kB05_V._Octave_Tutorial_Week_2/03_Computing_on_Data_13_min.txt 11.3 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min_scandata.xml 11.3 kB03_III._Linear_Algebra_Review_Week_1_Optional/03_Matrix_Vector_Multiplication_14_min.txt 11.1 kB11_XI._Machine_Learning_System_Design_Week_6/05_Data_For_Machine_Learning_11_min.txt 11.0 kB02_II._Linear_Regression_with_One_Variable_Week_1/06_Gradient_Descent_Intuition_12_min.txt 11.0 kB15_XV._Anomaly_Detection_Week_9/03_Algorithm_12_min.txt 10.9 kB05_V._Octave_Tutorial_Week_2/05_Control_Statements-_for_while_if_statements_13_min.txt 10.9 kB.____padding_file/542 10.7 kB09_IX._Neural_Networks-_Learning_Week_5/02_Backpropagation_Algorithm_12_min.txt 10.6 kB02_II._Linear_Regression_with_One_Variable_Week_1/05_Gradient_Descent_11_min.txt 10.6 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/05_Regularization_and_Bias-Variance_11_min.txt 10.6 kB11_XI._Machine_Learning_System_Design_Week_6/03_Error_Metrics_for_Skewed_Classes_12_min.txt 10.4 kB14_XIV._Dimensionality_Reduction_Week_8/02_Motivation_II-_Visualization_6_min.srt 10.4 kB08_VIII._Neural_Networks-_Representation_Week_4/04_Model_Representation_II_12_min.txt 10.4 kB01_I._Introduction_Week_1/02_What_is_Machine_Learning_7_min.srt 10.4 kB06_VI._Logistic_Regression_Week_3/04_Cost_Function_11_min.txt 10.2 kB12_XII._Support_Vector_Machines_Week_7/02_Large_Margin_Intuition_11_min.txt 10.2 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.srt 10.2 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min_scandata.xml 10.1 kB01_I._Introduction_Week_1/01_Welcome_7_min.srt 10.1 kB02_II._Linear_Regression_with_One_Variable_Week_1/02_Cost_Function_8_min.srt 10.1 kB09_IX._Neural_Networks-_Learning_Week_5/08_Autonomous_Driving_7_min.srt 10.0 kB15_XV._Anomaly_Detection_Week_9/02_Gaussian_Distribution_10_min.txt 10.0 kB08_VIII._Neural_Networks-_Representation_Week_4/03_Model_Representation_I_12_min.txt 10.0 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/07_Normal_Equation_Noninvertibility_Optional_6_min.srt 10.0 kB14_XIV._Dimensionality_Reduction_Week_8/05_Choosing_the_Number_of_Principal_Components_11_min.txt 9.9 kB07_VII._Regularization_Week_3/03_Regularized_Linear_Regression_11_min.txt 9.7 kB16_XVI._Recommender_Systems_Week_9/03_Collaborative_Filtering_10_min.txt 9.7 kB03_III._Linear_Algebra_Review_Week_1_Optional/06_Inverse_and_Transpose_11_min.txt 9.5 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min_scandata.xml 9.5 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min_scandata.xml 9.5 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min_scandata.xml 9.5 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min.txt 9.5 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min.txt 9.4 kB07_VII._Regularization_Week_3/02_Cost_Function_10_min.txt 9.4 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min.txt 9.3 kB06_VI._Logistic_Regression_Week_3/05_Simplified_Cost_Function_and_Gradient_Descent_10_min.txt 9.3 kB03_III._Linear_Algebra_Review_Week_1_Optional/04_Matrix_Matrix_Multiplication_11_min.txt 9.3 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min_scandata.xml 9.2 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min_scandata.xml 9.2 kB02_II._Linear_Regression_with_One_Variable_Week_1/07_Gradient_Descent_For_Linear_Regression_10_min.txt 9.0 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min.txt 9.0 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min_scandata.xml 8.9 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min_scandata.xml 8.9 kB14_XIV._Dimensionality_Reduction_Week_8/03_Principal_Component_Analysis_Problem_Formulation_9_min.txt 8.8 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/04_Gradient_Descent_in_Practice_II_-_Learning_Rate_9_min.txt 8.7 kB02_II._Linear_Regression_with_One_Variable_Week_1/08_Whats_Next_6_min.srt 8.7 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min_djvu.txt 8.6 kB13_XIII._Clustering_Week_8/05_Choosing_the_Number_of_Clusters_8_min.txt 8.6 kB02_II._Linear_Regression_with_One_Variable_Week_1/03_Cost_Function_-_Intuition_I_11_min.txt 8.5 kB19_XIX._Conclusion/01_Summary_and_Thank_You_5_min.srt 8.3 kB07_VII._Regularization_Week_3/04_Regularized_Logistic_Regression_9_min.txt 8.2 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min_djvu.txt 8.2 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min.txt 8.1 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.srt 8.1 kB15_XV._Anomaly_Detection_Week_9/05_Anomaly_Detection_vs._Supervised_Learning_8_min.txt 8.0 kB13_XIII._Clustering_Week_8/04_Random_Initialization_8_min.txt 8.0 kB17_XVII._Large_Scale_Machine_Learning_Week_10/03_Mini-Batch_Gradient_Descent_6_min.srt 8.0 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/03_Gradient_Descent_in_Practice_I_-_Feature_Scaling_9_min.txt 7.9 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/04_Diagnosing_Bias_vs._Variance_8_min.txt 7.9 kB05_V._Octave_Tutorial_Week_2/04_Plotting_Data_10_min.txt 7.9 kB01_I._Introduction_Week_1/01_Welcome_7_min_djvu.txt 7.9 kB16_XVI._Recommender_Systems_Week_9/04_Collaborative_Filtering_Algorithm_9_min.txt 7.9 kB02_II._Linear_Regression_with_One_Variable_Week_1/04_Cost_Function_-_Intuition_II_9_min.txt 7.9 kB08_VIII._Neural_Networks-_Representation_Week_4/02_Neurons_and_the_Brain_8_min.txt 7.8 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min.txt 7.8 kB08_VIII._Neural_Networks-_Representation_Week_4/06_Examples_and_Intuitions_II_10_min.txt 7.8 kB16_XVI._Recommender_Systems_Week_9/06_Implementational_Detail-_Mean_Normalization_9_min.txt 7.8 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min_djvu.txt 7.8 kB16_XVI._Recommender_Systems_Week_9/05_Vectorization-_Low_Rank_Matrix_Factorization_8_min.txt 7.8 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min_djvu.txt 7.8 kB14_XIV._Dimensionality_Reduction_Week_8/06_Reconstruction_from_Compressed_Representation_4_min.srt 7.7 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min_scandata.xml 7.7 kB15_XV._Anomaly_Detection_Week_9/01_Problem_Motivation_8_min.txt 7.7 kB08_VIII._Neural_Networks-_Representation_Week_4/07_Multiclass_Classification_4_min.srt 7.6 kB03_III._Linear_Algebra_Review_Week_1_Optional/05_Matrix_Multiplication_Properties_9_min.txt 7.6 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/05_Features_and_Polynomial_Regression_8_min.txt 7.6 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min_scandata.xml 7.4 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min_scandata.xml 7.4 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min.txt 7.2 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.srt 7.2 kB01_I._Introduction_Week_1/02_What_is_Machine_Learning_7_min.txt 7.1 kB09_IX._Neural_Networks-_Learning_Week_5/06_Random_Initialization_7_min.txt 7.1 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min.txt 7.0 kB09_IX._Neural_Networks-_Learning_Week_5/04_Implementation_Note-_Unrolling_Parameters_8_min.txt 7.0 kB02_II._Linear_Regression_with_One_Variable_Week_1/01_Model_Representation_8_min.txt 7.0 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/07_Deciding_What_to_Do_Next_Revisited_7_min.txt 7.0 kB01_I._Introduction_Week_1/01_Welcome_7_min.txt 6.9 kB02_II._Linear_Regression_with_One_Variable_Week_1/02_Cost_Function_8_min.txt 6.9 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min_scandata.xml 6.8 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/02_Gradient_Descent_for_Multiple_Variables_5_min.srt 6.8 kB12_XII._Support_Vector_Machines_Week_7/01_Optimization_Objective_15_min_djvu.txt 6.6 kB08_VIII._Neural_Networks-_Representation_Week_4/01_Non-linear_Hypotheses_10_min_djvu.txt 6.6 kB06_VI._Logistic_Regression_Week_3/02_Hypothesis_Representation_7_min.txt 6.6 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min.txt 6.6 kB16_XVI._Recommender_Systems_Week_9/01_Problem_Formulation_8_min_djvu.txt 6.5 kB13_XIII._Clustering_Week_8/03_Optimization_Objective_7_min.txt 6.5 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/02_Evaluating_a_Hypothesis_8_min.txt 6.5 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min_djvu.txt 6.4 kB14_XIV._Dimensionality_Reduction_Week_8/01_Motivation_I-_Data_Compression_10_min_djvu.txt 6.3 kB09_IX._Neural_Networks-_Learning_Week_5/01_Cost_Function_7_min.txt 6.2 kB06_VI._Logistic_Regression_Week_3/01_Classification_8_min_djvu.txt 6.1 kB06_VI._Logistic_Regression_Week_3/07_Multiclass_Classification-_One-vs-all_6_min.txt 6.1 kB10_X._Advice_for_Applying_Machine_Learning_Week_6/01_Deciding_What_to_Try_Next_6_min.txt 6.1 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min_djvu.txt 6.0 kB02_II._Linear_Regression_with_One_Variable_Week_1/08_Whats_Next_6_min.txt 6.0 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/01_Multiple_Features_8_min_djvu.txt 6.0 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/07_Normal_Equation_Noninvertibility_Optional_6_min.txt 5.8 kB08_VIII._Neural_Networks-_Representation_Week_4/05_Examples_and_Intuitions_I_7_min.txt 5.8 kB17_XVII._Large_Scale_Machine_Learning_Week_10/03_Mini-Batch_Gradient_Descent_6_min.txt 5.7 kB11_XI._Machine_Learning_System_Design_Week_6/01_Prioritizing_What_to_Work_On_10_min_scandata.xml 5.6 kB03_III._Linear_Algebra_Review_Week_1_Optional/02_Addition_and_Scalar_Multiplication_7_min.txt 5.6 kB17_XVII._Large_Scale_Machine_Learning_Week_10/01_Learning_With_Large_Datasets_6_min.txt 5.5 kB07_VII._Regularization_Week_3/01_The_Problem_of_Overfitting_10_min_djvu.txt 5.3 kB14_XIV._Dimensionality_Reduction_Week_8/02_Motivation_II-_Visualization_6_min.txt 4.8 kB18_XVIII._Application_Example-_Photo_OCR/01_Problem_Description_and_Pipeline_7_min_djvu.txt 4.8 kB03_III._Linear_Algebra_Review_Week_1_Optional/01_Matrices_and_Vectors_9_min_djvu.txt 4.7 kB09_IX._Neural_Networks-_Learning_Week_5/08_Autonomous_Driving_7_min.txt 4.7 kB19_XIX._Conclusion/01_Summary_and_Thank_You_5_min.txt 4.6 kB05_V._Octave_Tutorial_Week_2/07_Working_on_and_Submitting_Programming_Exercises_4_min.srt 4.5 kB04_IV._Linear_Regression_with_Multiple_Variables_Week_2/02_Gradient_Descent_for_Multiple_Variables_5_min.txt 4.4 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min_djvu.txt 3.8 kB14_XIV._Dimensionality_Reduction_Week_8/06_Reconstruction_from_Compressed_Representation_4_min.txt 3.6 kB08_VIII._Neural_Networks-_Representation_Week_4/07_Multiclass_Classification_4_min.txt 3.5 kB13_XIII._Clustering_Week_8/01_Unsupervised_Learning-_Introduction_3_min.txt 3.5 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min_scandata.xml 3.2 kB05_V._Octave_Tutorial_Week_2/07_Working_on_and_Submitting_Programming_Exercises_4_min.txt 3.1 kB05_V._Octave_Tutorial_Week_2/01_Basic_Operations_14_min_djvu.txt 1.3 kBacademictorrents_e8b1f9c5bf555fe58bc73addb83457dd6da69630_meta.xml 1.1 kB.____padding_file/290 608 Bytesacademictorrents_e8b1f9c5bf555fe58bc73addb83457dd6da69630.bib 121 Bytes