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[CourseClub.NET] Coursera - Machine Learning
大小 1.82 GB
文件数 229
Info Hash: EB46B659343D7111E04FF448748E9542BA50C169
收录时间 2026-01-04 17:28:01
更新时间 2026-01-04 17:49:28
文件列表 (229)
001.Welcome/001. Welcome to Machine Learning!.mp4
9.13 MB
001.Welcome/001. Welcome to Machine Learning!.srt
2.39 KB
002.Introduction/002. Welcome.mp4
18.28 MB
002.Introduction/002. Welcome.srt
9.52 KB
002.Introduction/003. What is Machine Learning.mp4
11.41 MB
002.Introduction/003. What is Machine Learning.srt
10.99 KB
002.Introduction/004. Supervised Learning.mp4
16.68 MB
002.Introduction/004. Supervised Learning.srt
18.87 KB
002.Introduction/005. Unsupervised Learning.mp4
23.33 MB
002.Introduction/005. Unsupervised Learning.srt
27.45 KB
003.Model and Cost Function/006. Model Representation.mp4
11.42 MB
003.Model and Cost Function/006. Model Representation.srt
9.58 KB
003.Model and Cost Function/007. Cost Function.mp4
11.51 MB
003.Model and Cost Function/007. Cost Function.srt
10.18 KB
003.Model and Cost Function/008. Cost Function - Intuition I.mp4
15.53 MB
003.Model and Cost Function/008. Cost Function - Intuition I.srt
11.74 KB
003.Model and Cost Function/009. Cost Function - Intuition II.mp4
16.99 MB
003.Model and Cost Function/009. Cost Function - Intuition II.srt
10.79 KB
004.Parameter Learning/010. Gradient Descent.mp4
18.72 MB
004.Parameter Learning/010. Gradient Descent.srt
16.31 KB
004.Parameter Learning/011. Gradient Descent Intuition.mp4
16.61 MB
004.Parameter Learning/011. Gradient Descent Intuition.srt
15.94 KB
004.Parameter Learning/012. Gradient Descent For Linear Regression.mp4
16.43 MB
004.Parameter Learning/012. Gradient Descent For Linear Regression.srt
13.4 KB
005.Linear Algebra Review/013. Matrices and Vectors.mp4
11.94 MB
005.Linear Algebra Review/013. Matrices and Vectors.srt
14.94 KB
005.Linear Algebra Review/014. Addition and Scalar Multiplication.mp4
9.27 MB
005.Linear Algebra Review/014. Addition and Scalar Multiplication.srt
11.28 KB
005.Linear Algebra Review/015. Matrix Vector Multiplication.mp4
18.93 MB
005.Linear Algebra Review/015. Matrix Vector Multiplication.srt
22.84 KB
005.Linear Algebra Review/016. Matrix Matrix Multiplication.mp4
16.29 MB
005.Linear Algebra Review/016. Matrix Matrix Multiplication.srt
13.66 KB
005.Linear Algebra Review/017. Matrix Multiplication Properties.mp4
12.15 MB
005.Linear Algebra Review/017. Matrix Multiplication Properties.srt
11.49 KB
005.Linear Algebra Review/018. Inverse and Transpose.mp4
17.01 MB
005.Linear Algebra Review/018. Inverse and Transpose.srt
19.86 KB
006.Multivariate Linear Regression/019. Multiple Features.mp4
11.58 MB
006.Multivariate Linear Regression/019. Multiple Features.srt
13.71 KB
006.Multivariate Linear Regression/020. Gradient Descent for Multiple Variables.mp4
7.62 MB
006.Multivariate Linear Regression/020. Gradient Descent for Multiple Variables.srt
6.37 KB
006.Multivariate Linear Regression/021. Gradient Descent in Practice I - Feature Scaling.mp4
12.94 MB
006.Multivariate Linear Regression/021. Gradient Descent in Practice I - Feature Scaling.srt
16.02 KB
006.Multivariate Linear Regression/022. Gradient Descent in Practice II - Learning Rate.mp4
12.56 MB
006.Multivariate Linear Regression/022. Gradient Descent in Practice II - Learning Rate.srt
12.48 KB
006.Multivariate Linear Regression/023. Features and Polynomial Regression.mp4
11.54 MB
006.Multivariate Linear Regression/023. Features and Polynomial Regression.srt
14.99 KB
007.Computing Parameters Analytically/024. Normal Equation.mp4
23.63 MB
007.Computing Parameters Analytically/024. Normal Equation.srt
29.45 KB
007.Computing Parameters Analytically/025. Normal Equation Noninvertibility.mp4
8.8 MB
007.Computing Parameters Analytically/025. Normal Equation Noninvertibility.srt
8.65 KB
008.Submitting Programming Assignments/026. Working on and Submitting Programming Assignments.mp4
8.96 MB
008.Submitting Programming Assignments/026. Working on and Submitting Programming Assignments.srt
4.26 KB
009.Octave Matlab Tutorial/027. Basic Operations.mp4
24.9 MB
009.Octave Matlab Tutorial/027. Basic Operations.srt
23.89 KB
009.Octave Matlab Tutorial/028. Moving Data Around.mp4
29.53 MB
009.Octave Matlab Tutorial/028. Moving Data Around.srt
26.94 KB
009.Octave Matlab Tutorial/029. Computing on Data.mp4
19.81 MB
009.Octave Matlab Tutorial/029. Computing on Data.srt
16.68 KB
009.Octave Matlab Tutorial/030. Plotting Data.mp4
20.08 MB
009.Octave Matlab Tutorial/030. Plotting Data.srt
16.34 KB
009.Octave Matlab Tutorial/031. Control Statements for, while, if statement.mp4
23.88 MB
009.Octave Matlab Tutorial/031. Control Statements for, while, if statement.srt
22.02 KB
009.Octave Matlab Tutorial/032. Vectorization.mp4
22.27 MB
009.Octave Matlab Tutorial/032. Vectorization.srt
17.32 KB
010.Classification and Representation/033. Classification.mp4
11.32 MB
010.Classification and Representation/033. Classification.srt
11.43 KB
010.Classification and Representation/034. Hypothesis Representation.mp4
11.17 MB
010.Classification and Representation/034. Hypothesis Representation.srt
9.61 KB
010.Classification and Representation/035. Decision Boundary.mp4
22.19 MB
010.Classification and Representation/035. Decision Boundary.srt
17.88 KB
011.Logistic Regression Model/036. Cost Function.mp4
15.83 MB
011.Logistic Regression Model/036. Cost Function.srt
13.37 KB
011.Logistic Regression Model/037. Simplified Cost Function and Gradient Descent.mp4
16.26 MB
011.Logistic Regression Model/037. Simplified Cost Function and Gradient Descent.srt
13.96 KB
011.Logistic Regression Model/038. Advanced Optimization.mp4
26.77 MB
011.Logistic Regression Model/038. Advanced Optimization.srt
26.27 KB
012.Multiclass Classification/039. Multiclass Classification One-vs-all.mp4
9.07 MB
012.Multiclass Classification/039. Multiclass Classification One-vs-all.srt
9.24 KB
013.Solving the Problem of Overfitting/040. The Problem of Overfitting.mp4
14.93 MB
013.Solving the Problem of Overfitting/040. The Problem of Overfitting.srt
18.19 KB
013.Solving the Problem of Overfitting/041. Cost Function.mp4
15.51 MB
013.Solving the Problem of Overfitting/041. Cost Function.srt
18.61 KB
013.Solving the Problem of Overfitting/042. Regularized Linear Regression.mp4
15.63 MB
013.Solving the Problem of Overfitting/042. Regularized Linear Regression.srt
14.18 KB
013.Solving the Problem of Overfitting/043. Regularized Logistic Regression.mp4
16.77 MB
013.Solving the Problem of Overfitting/043. Regularized Logistic Regression.srt
16.19 KB
014.Motivations/044. Non-linear Hypotheses.mp4
14.74 MB
014.Motivations/044. Non-linear Hypotheses.srt
17.95 KB
014.Motivations/045. Neurons and the Brain.mp4
14.57 MB
014.Motivations/045. Neurons and the Brain.srt
15.48 KB
015.Neural Networks/046. Model Representation I.mp4
18 MB
015.Neural Networks/046. Model Representation I.srt
14.42 KB
015.Neural Networks/047. Model Representation II.mp4
18.4 MB
015.Neural Networks/047. Model Representation II.srt
21.13 KB
016.Applications/048. Examples and Intuitions I.mp4
10.07 MB
016.Applications/048. Examples and Intuitions I.srt
8.51 KB
016.Applications/049. Examples and Intuitions II.mp4
20.93 MB
016.Applications/049. Examples and Intuitions II.srt
11.44 KB
016.Applications/050. Multiclass Classification.mp4
7 MB
016.Applications/050. Multiclass Classification.srt
7 KB
017.Cost Function and Backpropagation/051. Cost Function.mp4
10.25 MB
017.Cost Function and Backpropagation/051. Cost Function.srt
8.87 KB
017.Cost Function and Backpropagation/052. Backpropagation Algorithm.mp4
19.07 MB
017.Cost Function and Backpropagation/052. Backpropagation Algorithm.srt
21.51 KB
017.Cost Function and Backpropagation/053. Backpropagation Intuition.mp4
22.23 MB
017.Cost Function and Backpropagation/053. Backpropagation Intuition.srt
17.68 KB
018.Backpropagation in Practice/054. Implementation Note Unrolling Parameters.mp4
12.92 MB
018.Backpropagation in Practice/054. Implementation Note Unrolling Parameters.srt
14.04 KB
018.Backpropagation in Practice/055. Gradient Checking.mp4
18.35 MB
018.Backpropagation in Practice/055. Gradient Checking.srt
16.96 KB
018.Backpropagation in Practice/056. Random Initialization.mp4
9.81 MB
018.Backpropagation in Practice/056. Random Initialization.srt
10.35 KB
018.Backpropagation in Practice/057. Putting It Together.mp4
23.55 MB
018.Backpropagation in Practice/057. Putting It Together.srt
26.13 KB
019.Application of Neural Networks/058. Autonomous Driving.mp4
28.3 MB
019.Application of Neural Networks/058. Autonomous Driving.srt
6.88 KB
020.Evaluating a Learning Algorithm/059. Deciding What to Try Next.mp4
9.35 MB
020.Evaluating a Learning Algorithm/059. Deciding What to Try Next.srt
11.74 KB
020.Evaluating a Learning Algorithm/060. Evaluating a Hypothesis.mp4
11.05 MB
020.Evaluating a Learning Algorithm/060. Evaluating a Hypothesis.srt
10.94 KB
020.Evaluating a Learning Algorithm/061. Model Selection and Train Validation Test Sets.mp4
19.04 MB
020.Evaluating a Learning Algorithm/061. Model Selection and Train Validation Test Sets.srt
16.93 KB
021.Bias vs. Variance/062. Diagnosing Bias vs. Variance.mp4
12.18 MB
021.Bias vs. Variance/062. Diagnosing Bias vs. Variance.srt
11.21 KB
021.Bias vs. Variance/063. Regularization and Bias Variance.mp4
16.39 MB
021.Bias vs. Variance/063. Regularization and Bias Variance.srt
14.92 KB
021.Bias vs. Variance/064. Learning Curves.mp4
16.39 MB
021.Bias vs. Variance/064. Learning Curves.srt
23.34 KB
021.Bias vs. Variance/065. Deciding What to Do Next Revisited.mp4
11.43 MB
021.Bias vs. Variance/065. Deciding What to Do Next Revisited.srt
13.31 KB
022.Building a Spam Classifier/066. Prioritizing What to Work On.mp4
15.06 MB
022.Building a Spam Classifier/066. Prioritizing What to Work On.srt
18.54 KB
022.Building a Spam Classifier/067. Error Analysis.mp4
21.27 MB
022.Building a Spam Classifier/067. Error Analysis.srt
19.29 KB
023.Handling Skewed Data/068. Error Metrics for Skewed Classes.mp4
17.95 MB
023.Handling Skewed Data/068. Error Metrics for Skewed Classes.srt
20.8 KB
023.Handling Skewed Data/069. Trading Off Precision and Recall.mp4
21.3 MB
023.Handling Skewed Data/069. Trading Off Precision and Recall.srt
19.67 KB
024.Using Large Data Sets/070. Data For Machine Learning.mp4
17.31 MB
024.Using Large Data Sets/070. Data For Machine Learning.srt
21.85 KB
025.Large Margin Classification/071. Optimization Objective.mp4
21.89 MB
025.Large Margin Classification/071. Optimization Objective.srt
19.83 KB
025.Large Margin Classification/072. Large Margin Intuition.mp4
15.21 MB
025.Large Margin Classification/072. Large Margin Intuition.srt
20.07 KB
025.Large Margin Classification/073. Mathematics Behind Large Margin Classification.mp4
28.48 MB
025.Large Margin Classification/073. Mathematics Behind Large Margin Classification.srt
33.8 KB
026.Kernels/074. Kernels I.mp4
22.81 MB
026.Kernels/074. Kernels I.srt
27.38 KB
026.Kernels/075. Kernels II.mp4
22.63 MB
026.Kernels/075. Kernels II.srt
28.95 KB
027.SVMs in Practice/076. Using An SVM.mp4
31.99 MB
027.SVMs in Practice/076. Using An SVM.srt
41.09 KB
028.Clustering/077. Unsupervised Learning Introduction.mp4
5.16 MB
028.Clustering/077. Unsupervised Learning Introduction.srt
5.01 KB
028.Clustering/078. K-Means Algorithm.mp4
17.67 MB
028.Clustering/078. K-Means Algorithm.srt
24.74 KB
028.Clustering/079. Optimization Objective.mp4
10.92 MB
028.Clustering/079. Optimization Objective.srt
9.25 KB
028.Clustering/080. Random Initialization.mp4
11.15 MB
028.Clustering/080. Random Initialization.srt
15.33 KB
028.Clustering/081. Choosing the Number of Clusters.mp4
12.22 MB
028.Clustering/081. Choosing the Number of Clusters.srt
16.92 KB
029.Motivation/082. Motivation I Data Compression.mp4
21.45 MB
029.Motivation/082. Motivation I Data Compression.srt
18.98 KB
029.Motivation/083. Motivation II Visualization.mp4
8.3 MB
029.Motivation/083. Motivation II Visualization.srt
9.59 KB
030.Principal Component Analysis/084. Principal Component Analysis Problem Formulation.mp4
13.98 MB
030.Principal Component Analysis/084. Principal Component Analysis Problem Formulation.srt
13.05 KB
030.Principal Component Analysis/085. Principal Component Analysis Algorithm.mp4
24.29 MB
030.Principal Component Analysis/085. Principal Component Analysis Algorithm.srt
26.91 KB
031.Applying PCA/086. Reconstruction from Compressed Representation.mp4
7.16 MB
031.Applying PCA/086. Reconstruction from Compressed Representation.srt
5.08 KB
031.Applying PCA/087. Choosing the Number of Principal Components.mp4
15.64 MB
031.Applying PCA/087. Choosing the Number of Principal Components.srt
19.92 KB
031.Applying PCA/088. Advice for Applying PCA.mp4
19.74 MB
031.Applying PCA/088. Advice for Applying PCA.srt
24.83 KB
032.Density Estimation/089. Problem Motivation.mp4
10.56 MB
032.Density Estimation/089. Problem Motivation.srt
15.11 KB
032.Density Estimation/090. Gaussian Distribution.mp4
15.19 MB
032.Density Estimation/090. Gaussian Distribution.srt
14.54 KB
032.Density Estimation/091. Algorithm.mp4
18.94 MB
032.Density Estimation/091. Algorithm.srt
22.13 KB
033.Building an Anomaly Detection System/092. Developing and Evaluating an Anomaly Detection System.mp4
20.53 MB
033.Building an Anomaly Detection System/092. Developing and Evaluating an Anomaly Detection System.srt
25.77 KB
033.Building an Anomaly Detection System/093. Anomaly Detection vs. Supervised Learning.mp4
13.15 MB
033.Building an Anomaly Detection System/093. Anomaly Detection vs. Supervised Learning.srt
11.23 KB
033.Building an Anomaly Detection System/094. Choosing What Features to Use.mp4
19.09 MB
033.Building an Anomaly Detection System/094. Choosing What Features to Use.srt
23.72 KB
034.Multivariate Gaussian Distribution (Optional)/095. Multivariate Gaussian Distribution.mp4
21.86 MB
034.Multivariate Gaussian Distribution (Optional)/095. Multivariate Gaussian Distribution.srt
25.84 KB
034.Multivariate Gaussian Distribution (Optional)/096. Anomaly Detection using the Multivariate Gaussian Distribution.mp4
22.42 MB
034.Multivariate Gaussian Distribution (Optional)/096. Anomaly Detection using the Multivariate Gaussian Distribution.srt
24.84 KB
035.Predicting Movie Ratings/097. Problem Formulation.mp4
16.41 MB
035.Predicting Movie Ratings/097. Problem Formulation.srt
15.87 KB
035.Predicting Movie Ratings/098. Content Based Recommendations.mp4
23.19 MB
035.Predicting Movie Ratings/098. Content Based Recommendations.srt
19.51 KB
036.Collaborative Filtering/099. Collaborative Filtering.mp4
15.52 MB
036.Collaborative Filtering/099. Collaborative Filtering.srt
19.09 KB
036.Collaborative Filtering/100. Collaborative Filtering Algorithm.mp4
14.71 MB
036.Collaborative Filtering/100. Collaborative Filtering Algorithm.srt
15.55 KB
037.Low Rank Matrix Factorization/101. Vectorization Low Rank Matrix Factorization.mp4
12.82 MB
037.Low Rank Matrix Factorization/101. Vectorization Low Rank Matrix Factorization.srt
15.38 KB
037.Low Rank Matrix Factorization/102. Implementational Detail Mean Normalization.mp4
12.91 MB
037.Low Rank Matrix Factorization/102. Implementational Detail Mean Normalization.srt
15.63 KB
038.Gradient Descent with Large Datasets/103. Learning With Large Datasets.mp4
8.54 MB
038.Gradient Descent with Large Datasets/103. Learning With Large Datasets.srt
7.59 KB
038.Gradient Descent with Large Datasets/104. Stochastic Gradient Descent.mp4
20.99 MB
038.Gradient Descent with Large Datasets/104. Stochastic Gradient Descent.srt
17.57 KB
038.Gradient Descent with Large Datasets/105. Mini-Batch Gradient Descent.mp4
9.75 MB
038.Gradient Descent with Large Datasets/105. Mini-Batch Gradient Descent.srt
7.54 KB
038.Gradient Descent with Large Datasets/106. Stochastic Gradient Descent Convergence.mp4
18.11 MB
038.Gradient Descent with Large Datasets/106. Stochastic Gradient Descent Convergence.srt
15.67 KB
039.Advanced Topics/107. Online Learning.mp4
20.51 MB
039.Advanced Topics/107. Online Learning.srt
26.09 KB
039.Advanced Topics/108. Map Reduce and Data Parallelism.mp4
21.23 MB
039.Advanced Topics/108. Map Reduce and Data Parallelism.srt
27.22 KB
040.Photo OCR/109. Problem Description and Pipeline.mp4
10.42 MB
040.Photo OCR/109. Problem Description and Pipeline.srt
13.88 KB
040.Photo OCR/110. Sliding Windows.mp4
21.93 MB
040.Photo OCR/110. Sliding Windows.srt
29.68 KB
040.Photo OCR/111. Getting Lots of Data and Artificial Data.mp4
25.3 MB
040.Photo OCR/111. Getting Lots of Data and Artificial Data.srt
33.19 KB
040.Photo OCR/112. Ceiling Analysis What Part of the Pipeline to Work on Next.mp4
21.92 MB
040.Photo OCR/112. Ceiling Analysis What Part of the Pipeline to Work on Next.srt
21.77 KB
041.Conclusion/113. Summary and Thank You.mp4
9.08 MB
041.Conclusion/113. Summary and Thank You.srt
7.7 KB
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123 B
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133 B
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