[Coursera] Machine Learning

Magnet Download

Category Other
Type Tutorials
Language
Total size 1.8 GB
Uploaded By CourseClub

Downloads 2440
Last checked 10 hours ago
Date uploaded 10 hours ago
Seeders 9
Leechers 3

Info Hash : EB46B659343D7111E04FF448748E9542BA50C169

Tracker list
Files

                        Files: 

                        [Coursera] Machine Learning
                        udp://62.138.0.158:6969/announce
udp://87.233.192.220:6969/announce
udp://88.198.231.1:1337/announce
udp://151.80.120.113:2710/announce
udp://111.6.78.96:6969/announce
udp://90.179.64.91:1337/announce
udp://51.15.4.13:1337/announce
udp://191.96.249.23:6969/announce
udp://35.187.36.248:1337/announce
udp://123.249.16.65:2710/announce
udp://127.0.0.1:6969/announce
udp://210.244.71.25:6969/announce
udp://78.142.19.42:1337/announce
udp://173.254.219.72:6969/announce
udp://51.15.76.199:6969/announce
udp://91.212.150.191:3418/announce
udp://103.224.212.222:6969/announce
udp://92.241.171.245:6969/announce
udp://51.15.40.114:80/announce
udp://37.19.5.139:6969/announce


                     

Code:

001. Welcome to Machine Learning!.mp4 (9.1 MB)
001. Welcome to Machine Learning!.srt (2.4 KB)
002. Welcome.mp4 (18.3 MB)
002. Welcome.srt (9.5 KB)
003. What is Machine Learning.mp4 (11.4 MB)
003. What is Machine Learning.srt (11.0 KB)
004. Supervised Learning.mp4 (16.7 MB)
004. Supervised Learning.srt (18.9 KB)
005. Unsupervised Learning.mp4 (23.3 MB)
005. Unsupervised Learning.srt (27.5 KB)
006. Model Representation.mp4 (11.4 MB)
006. Model Representation.srt (9.6 KB)
007. Cost Function.mp4 (11.5 MB)
007. Cost Function.srt (10.2 KB)
008. Cost Function - Intuition I.mp4 (15.5 MB)
008. Cost Function - Intuition I.srt (11.7 KB)
009. Cost Function - Intuition II.mp4 (17.0 MB)
009. Cost Function - Intuition II.srt (10.8 KB)
010. Gradient Descent.mp4 (18.7 MB)
010. Gradient Descent.srt (16.3 KB)
011. Gradient Descent Intuition.mp4 (16.6 MB)
011. Gradient Descent Intuition.srt (15.9 KB)
012. Gradient Descent For Linear Regression.mp4 (16.4 MB)
012. Gradient Descent For Linear Regression.srt (13.4 KB)
013. Matrices and Vectors.mp4 (11.9 MB)
013. Matrices and Vectors.srt (14.9 KB)
014. Addition and Scalar Multiplication.mp4 (9.3 MB)
014. Addition and Scalar Multiplication.srt (11.3 KB)
015. Matrix Vector Multiplication.mp4 (18.9 MB)
015. Matrix Vector Multiplication.srt (22.8 KB)
016. Matrix Matrix Multiplication.mp4 (16.3 MB)
016. Matrix Matrix Multiplication.srt (13.7 KB)
017. Matrix Multiplication Properties.mp4 (12.2 MB)
017. Matrix Multiplication Properties.srt (11.5 KB)
018. Inverse and Transpose.mp4 (17.0 MB)
018. Inverse and Transpose.srt (19.9 KB)
019. Multiple Features.mp4 (11.6 MB)
019. Multiple Features.srt (13.7 KB)
020. Gradient Descent for Multiple Variables.mp4 (7.6 MB)
020. Gradient Descent for Multiple Variables.srt (6.4 KB)
021. Gradient Descent in Practice I - Feature Scaling.mp4 (12.9 MB)
021. Gradient Descent in Practice I - Feature Scaling.srt (16.0 KB)
022. Gradient Descent in Practice II - Learning Rate.mp4 (12.6 MB)
022. Gradient Descent in Practice II - Learning Rate.srt (12.5 KB)
023. Features and Polynomial Regression.mp4 (11.5 MB)
023. Features and Polynomial Regression.srt (15.0 KB)
024. Normal Equation.mp4 (23.6 MB)
024. Normal Equation.srt (29.5 KB)
025. Normal Equation Noninvertibility.mp4 (8.8 MB)
025. Normal Equation Noninvertibility.srt (8.6 KB)
026. Working on and Submitting Programming Assignments.mp4 (9.0 MB)
026. Working on and Submitting Programming Assignments.srt (4.3 KB)
027. Basic Operations.mp4 (24.9 MB)
027. Basic Operations.srt (23.9 KB)
028. Moving Data Around.mp4 (29.5 MB)
028. Moving Data Around.srt (26.9 KB)
029. Computing on Data.mp4 (19.8 MB)
029. Computing on Data.srt (16.7 KB)
030. Plotting Data.mp4 (20.1 MB)
030. Plotting Data.srt (16.3 KB)
031. Control Statements for, while, if statement.mp4 (23.9 MB)
031. Control Statements for, while, if statement.srt (22.0 KB)
032. Vectorization.mp4 (22.3 MB)
032. Vectorization.srt (17.3 KB)
033. Classification.mp4 (11.3 MB)
033. Classification.srt (11.4 KB)
034. Hypothesis Representation.mp4 (11.2 MB)
034. Hypothesis Representation.srt (9.6 KB)
035. Decision Boundary.mp4 (22.2 MB)
035. Decision Boundary.srt (17.9 KB)
036. Cost Function.mp4 (15.8 MB)
036. Cost Function.srt (13.4 KB)
037. Simplified Cost Function and Gradient Descent.mp4 (16.3 MB)
037. Simplified Cost Function and Gradient Descent.srt (14.0 KB)
038. Advanced Optimization.mp4 (26.8 MB)
038. Advanced Optimization.srt (26.3 KB)
039. Multiclass Classification One-vs-all.mp4 (9.1 MB)
039. Multiclass Classification One-vs-all.srt (9.2 KB)
040. The Problem of Overfitting.mp4 (14.9 MB)
040. The Problem of Overfitting.srt (18.2 KB)
041. Cost Function.mp4 (15.5 MB)
041. Cost Function.srt (18.6 KB)
042. Regularized Linear Regression.mp4 (15.6 MB)
042. Regularized Linear Regression.srt (14.2 KB)
043. Regularized Logistic Regression.mp4 (16.8 MB)
043. Regularized Logistic Regression.srt (16.2 KB)
044. Non-linear Hypotheses.mp4 (14.7 MB)
044. Non-linear Hypotheses.srt (18.0 KB)
045. Neurons and the Brain.mp4 (14.6 MB)
045. Neurons and the Brain.srt (15.5 KB)
046. Model Representation I.mp4 (18.0 MB)
046. Model Representation I.srt (14.4 KB)
047. Model Representation II.mp4 (18.4 MB)
047. Model Representation II.srt (21.1 KB)
048. Examples and Intuitions I.mp4 (10.1 MB)
048. Examples and Intuitions I.srt (8.5 KB)
049. Examples and Intuitions II.mp4 (20.9 MB)
049. Examples and Intuitions II.srt (11.4 KB)
050. Multiclass Classification.mp4 (7.0 MB)
050. Multiclass Classification.srt (7.0 KB)
051. Cost Function.mp4 (10.2 MB)
051. Cost Function.srt (8.9 KB)
052. Backpropagation Algorithm.mp4 (19.1 MB)
052. Backpropagation Algorithm.srt (21.5 KB)
053. Backpropagation Intuition.mp4 (22.2 MB)
053. Backpropagation Intuition.srt (17.7 KB)
054. Implementation Note Unrolling Parameters.mp4 (12.9 MB)
054. Implementation Note Unrolling Parameters.srt (14.0 KB)
055. Gradient Checking.mp4 (18.4 MB)
055. Gradient Checking.srt (17.0 KB)
056. Random Initialization.mp4 (9.8 MB)
056. Random Initialization.srt (10.3 KB)
057. Putting It Together.mp4 (23.5 MB)
057. Putting It Together.srt (26.1 KB)
058. Autonomous Driving.mp4 (28.3 MB)
058. Autonomous Driving.srt (6.9 KB)
059. Deciding What to Try Next.mp4 (9.4 MB)
059. Deciding What to Try Next.srt (11.7 KB)
060. Evaluating a Hypothesis.mp4 (11.0 MB)
060. Evaluating a Hypothesis.srt (10.9 KB)
061. Model Selection and Train Validation Test Sets.mp4 (19.0 MB)
061. Model Selection and Train Validation Test Sets.srt (16.9 KB)
062. Diagnosing Bias vs. Variance.mp4 (12.2 MB)
062. Diagnosing Bias vs. Variance.srt (11.2 KB)
063. Regularization and Bias Variance.mp4 (16.4 MB)
063. Regularization and Bias Variance.srt (14.9 KB)
064. Learning Curves.mp4 (16.4 MB)
064. Learning Curves.srt (23.3 KB)
065. Deciding What to Do Next Revisited.mp4 (11.4 MB)
065. Deciding What to Do Next Revisited.srt (13.3 KB)
066. Prioritizing What to Work On.mp4 (15.1 MB)
066. Prioritizing What to Work On.srt (18.5 KB)
067. Error Analysis.mp4 (21.3 MB)
067. Error Analysis.srt (19.3 KB)
068. Error Metrics for Skewed Classes.mp4 (17.9 MB)
068. Error Metrics for Skewed Classes.srt (20.8 KB)
069. Trading Off Precision and Recall.mp4 (21.3 MB)
069. Trading Off Precision and Recall.srt (19.7 KB)
070. Data For Machine Learning.mp4 (17.3 MB)
070. Data For Machine Learning.srt (21.8 KB)
071. Optimization Objective.mp4 (21.9 MB)
071. Optimization Objective.srt (19.8 KB)
072. Large Margin Intuition.mp4 (15.2 MB)
072. Large Margin Intuition.srt (20.1 KB)
073. Mathematics Behind Large Margin Classification.mp4 (28.5 MB)
073. Mathematics Behind Large Margin Classification.srt (33.8 KB)
074. Kernels I.mp4 (22.8 MB)
074. Kernels I.srt (27.4 KB)
075. Kernels II.mp4 (22.6 MB)
075. Kernels II.srt (29.0 KB)
076. Using An SVM.mp4 (32.0 MB)
076. Using An SVM.srt (41.1 KB)
077. Unsupervised Learning Introduction.mp4 (5.2 MB)
077. Unsupervised Learning Introduction.srt (5.0 KB)
078. K-Means Algorithm.mp4 (17.7 MB)
078. K-Means Algorithm.srt (24.7 KB)
079. Optimization Objective.mp4 (10.9 MB)
079. Optimization Objective.srt (9.3 KB)
080. Random Initialization.mp4 (11.1 MB)
080. Random Initialization.srt (15.3 KB)
081. Choosing the Number of Clusters.mp4 (12.2 MB)
081. Choosing the Number of Clusters.srt (16.9 KB)
082. Motivation I Data Compression.mp4 (21.5 MB)
082. Motivation I Data Compression.srt (19.0 KB)
083. Motivation II Visualization.mp4 (8.3 MB)
083. Motivation II Visualization.srt (9.6 KB)
084. Principal Component Analysis Problem Formulation.mp4 (14.0 MB)
084. Principal Component Analysis Problem Formulation.srt (13.0 KB)
085. Principal Component Analysis Algorithm.mp4 (24.3 MB)
085. Principal Component Analysis Algorithm.srt (26.9 KB)
086. Reconstruction from Compressed Representation.mp4 (7.2 MB)
086. Reconstruction from Compressed Representation.srt (5.1 KB)
087. Choosing the Number of Principal Components.mp4 (15.6 MB)
087. Choosing the Number of Principal Components.srt (19.9 KB)
088. Advice for Applying PCA.mp4 (19.7 MB)
088. Advice for Applying PCA.srt (24.8 KB)
089. Problem Motivation.mp4 (10.6 MB)
089. Problem Motivation.srt (15.1 KB)
090. Gaussian Distribution.mp4 (15.2 MB)
090. Gaussian Distribution.srt (14.5 KB)
091. Algorithm.mp4 (18.9 MB)
091. Algorithm.srt (22.1 KB)
092. Developing and Evaluating an Anomaly Detection System.mp4 (20.5 MB)
092. Developing and Evaluating an Anomaly Detection System.srt (25.8 KB)
093. Anomaly Detection vs. Supervised Learning.mp4 (13.1 MB)
093. Anomaly Detection vs. Supervised Learning.srt (11.2 KB)
094. Choosing What Features to Use.mp4 (19.1 MB)
094. Choosing What Features to Use.srt (23.7 KB)
095. Multivariate Gaussian Distribution.mp4 (21.9 MB)
095. Multivariate Gaussian Distribution.srt (25.8 KB)
096. Anomaly Detection using the Multivariate Gaussian Distribution.mp4 (22.4 MB)
096. Anomaly Detection using the Multivariate Gaussian Distribution.srt (24.8 KB)
097. Problem Formulation.mp4 (16.4 MB)
097. Problem Formulation.srt (15.9 KB)
098. Content Based Recommendations.mp4 (23.2 MB)
098. Content Based Recommendations.srt (19.5 KB)
099. Collaborative Filtering.mp4 (15.5 MB)
099. Collaborative Filtering.srt (19.1 KB)
100. Collaborative Filtering Algorithm.mp4 (14.7 MB)
100. Collaborative Filtering Algorithm.srt (15.6 KB)
101. Vectorization Low Rank Matrix Factorization.mp4 (12.8 MB)
101. Vectorization Low Rank Matrix Factorization.srt (15.4 KB)
102. Implementational Detail Mean Normalization.mp4 (12.9 MB)
102. Implementational Detail Mean Normalization.srt (15.6 KB)
103. Learning With Large Datasets.mp4 (8.5 MB)
103. Learning With Large Datasets.srt (7.6 KB)
104. Stochastic Gradient Descent.mp4 (21.0 MB)
104. Stochastic Gradient Descent.srt (17.6 KB)
105. Mini-Batch Gradient Descent.mp4 (9.8 MB)
105. Mini-Batch Gradient Descent.srt (7.5 KB)
106. Stochastic Gradient Descent Convergence.mp4 (18.1 MB)
106. Stochastic Gradient Descent Convergence.srt (15.7 KB)
107. Online Learning.mp4 (20.5 MB)
107. Online Learning.srt (26.1 KB)
108. Map Reduce and Data Parallelism.mp4 (21.2 MB)
108. Map Reduce and Data Parallelism.srt (27.2 KB)
109. Problem Description and Pipeline.mp4 (10.4 MB)
109. Problem Description and Pipeline.srt (13.9 KB)
110. Sliding Windows.mp4 (21.9 MB)
110. Sliding Windows.srt (29.7 KB)
111. Getting Lots of Data and Artificial Data.mp4 (25.3 MB)
111. Getting Lots of Data and Artificial Data.srt (33.2 KB)
112. Ceiling Analysis What Part of the Pipeline to Work on Next.mp4 (21.9 MB)
112. Ceiling Analysis What Part of the Pipeline to Work on Next.srt (21.8 KB)
113. Summary and Thank You.mp4 (9.1 MB)
113. Summary and Thank You.srt (7.7 KB)
[CourseClub.NET].url (0.1 KB)
[FCS Forum].url (0.1 KB)
[FreeCourseSite.com].url (0.1 KB)