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TORRENT DETAILS

[CourseClub.NET] Coursera - Machine Learning

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	eb46b659343d7111e04ff448748e9542ba50c169
Size:	1.8 GB in 99 files
Release Date(s):	Torrent Release: 23-09-2018 by user
Swarm:	0 Seeds & 0 Peers
Vote:	No votes yet.

DESCRIPTION

[Coursera] Machine Learning

Machine learning is the science of getting computers to act without being explicitly programmed.

For More Courses: https://courseclub.net

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FILE LIST

Filename		Size
	001.Welcome/001. Welcome to Machine Learning!.mp4	9.1 MB
	001.Welcome/001. Welcome to Machine Learning!.srt	2.4 KB
	002.Introduction/002. Welcome.mp4	18.3 MB
	002.Introduction/002. Welcome.srt	9.5 KB
	002.Introduction/003. What is Machine Learning.mp4	11.4 MB
	002.Introduction/003. What is Machine Learning.srt	11 KB
	002.Introduction/004. Supervised Learning.mp4	16.7 MB
	002.Introduction/004. Supervised Learning.srt	18.9 KB
	002.Introduction/005. Unsupervised Learning.mp4	23.3 MB
	002.Introduction/005. Unsupervised Learning.srt	27.5 KB
	003.Model and Cost Function/006. Model Representation.mp4	11.4 MB
	003.Model and Cost Function/006. Model Representation.srt	9.6 KB
	003.Model and Cost Function/007. Cost Function.mp4	11.5 MB
	003.Model and Cost Function/007. Cost Function.srt	10.2 KB
	003.Model and Cost Function/008. Cost Function - Intuition I.mp4	15.5 MB
	003.Model and Cost Function/008. Cost Function - Intuition I.srt	11.7 KB
	003.Model and Cost Function/009. Cost Function - Intuition II.mp4	17 MB
	003.Model and Cost Function/009. Cost Function - Intuition II.srt	10.8 KB
	004.Parameter Learning/010. Gradient Descent.mp4	18.7 MB
	004.Parameter Learning/010. Gradient Descent.srt	16.3 KB
	004.Parameter Learning/011. Gradient Descent Intuition.mp4	16.6 MB
	004.Parameter Learning/011. Gradient Descent Intuition.srt	15.9 KB
	004.Parameter Learning/012. Gradient Descent For Linear Regression.mp4	16.4 MB
	004.Parameter Learning/012. Gradient Descent For Linear Regression.srt	13.4 KB
	005.Linear Algebra Review/013. Matrices and Vectors.mp4	11.9 MB
	005.Linear Algebra Review/013. Matrices and Vectors.srt	14.9 KB
	005.Linear Algebra Review/014. Addition and Scalar Multiplication.mp4	9.3 MB
	005.Linear Algebra Review/014. Addition and Scalar Multiplication.srt	11.3 KB
	005.Linear Algebra Review/015. Matrix Vector Multiplication.mp4	18.9 MB
	005.Linear Algebra Review/015. Matrix Vector Multiplication.srt	22.8 KB
	005.Linear Algebra Review/016. Matrix Matrix Multiplication.mp4	16.3 MB
	005.Linear Algebra Review/016. Matrix Matrix Multiplication.srt	13.7 KB
	005.Linear Algebra Review/017. Matrix Multiplication Properties.mp4	12.2 MB
	005.Linear Algebra Review/017. Matrix Multiplication Properties.srt	11.5 KB
	005.Linear Algebra Review/018. Inverse and Transpose.mp4	17 MB
	005.Linear Algebra Review/018. Inverse and Transpose.srt	19.9 KB
	006.Multivariate Linear Regression/019. Multiple Features.mp4	11.6 MB
	006.Multivariate Linear Regression/019. Multiple Features.srt	13.7 KB
	006.Multivariate Linear Regression/020. Gradient Descent for Multiple Variables.mp4	7.6 MB
	006.Multivariate Linear Regression/020. Gradient Descent for Multiple Variables.srt	6.4 KB
	006.Multivariate Linear Regression/021. Gradient Descent in Practice I - Feature Scaling.mp4	12.9 MB
	006.Multivariate Linear Regression/021. Gradient Descent in Practice I - Feature Scaling.srt	16 KB
	006.Multivariate Linear Regression/022. Gradient Descent in Practice II - Learning Rate.mp4	12.6 MB
	006.Multivariate Linear Regression/022. Gradient Descent in Practice II - Learning Rate.srt	12.5 KB
	006.Multivariate Linear Regression/023. Features and Polynomial Regression.mp4	11.5 MB
	006.Multivariate Linear Regression/023. Features and Polynomial Regression.srt	15 KB
	007.Computing Parameters Analytically/024. Normal Equation.mp4	23.6 MB
	007.Computing Parameters Analytically/024. Normal Equation.srt	29.5 KB
	007.Computing Parameters Analytically/025. Normal Equation Noninvertibility.mp4	8.8 MB
	007.Computing Parameters Analytically/025. Normal Equation Noninvertibility.srt	8.6 KB
	008.Submitting Programming Assignments/026. Working on and Submitting Programming Assignments.mp4	9 MB
	008.Submitting Programming Assignments/026. Working on and Submitting Programming Assignments.srt	4.3 KB
	009.Octave Matlab Tutorial/027. Basic Operations.mp4	24.9 MB
	009.Octave Matlab Tutorial/027. Basic Operations.srt	23.9 KB
	009.Octave Matlab Tutorial/028. Moving Data Around.mp4	29.5 MB
	009.Octave Matlab Tutorial/028. Moving Data Around.srt	26.9 KB
	009.Octave Matlab Tutorial/029. Computing on Data.mp4	19.8 MB
	009.Octave Matlab Tutorial/029. Computing on Data.srt	16.7 KB
	009.Octave Matlab Tutorial/030. Plotting Data.mp4	20.1 MB
	009.Octave Matlab Tutorial/030. Plotting Data.srt	16.3 KB
	009.Octave Matlab Tutorial/031. Control Statements for, while, if statement.mp4	23.9 MB
	009.Octave Matlab Tutorial/031. Control Statements for, while, if statement.srt	22 KB
	009.Octave Matlab Tutorial/032. Vectorization.mp4	22.3 MB
	009.Octave Matlab Tutorial/032. Vectorization.srt	17.3 KB
	010.Classification and Representation/033. Classification.mp4	11.3 MB
	010.Classification and Representation/033. Classification.srt	11.4 KB
	010.Classification and Representation/034. Hypothesis Representation.mp4	11.2 MB
	010.Classification and Representation/034. Hypothesis Representation.srt	9.6 KB
	010.Classification and Representation/035. Decision Boundary.mp4	22.2 MB
	010.Classification and Representation/035. Decision Boundary.srt	17.9 KB
	011.Logistic Regression Model/036. Cost Function.mp4	15.8 MB
	011.Logistic Regression Model/036. Cost Function.srt	13.4 KB
	011.Logistic Regression Model/037. Simplified Cost Function and Gradient Descent.mp4	16.3 MB
	011.Logistic Regression Model/037. Simplified Cost Function and Gradient Descent.srt	14 KB
	011.Logistic Regression Model/038. Advanced Optimization.mp4	26.8 MB
	011.Logistic Regression Model/038. Advanced Optimization.srt	26.3 KB
	012.Multiclass Classification/039. Multiclass Classification One-vs-all.mp4	9.1 MB
	012.Multiclass Classification/039. Multiclass Classification One-vs-all.srt	9.2 KB
	013.Solving the Problem of Overfitting/040. The Problem of Overfitting.mp4	14.9 MB
	013.Solving the Problem of Overfitting/040. The Problem of Overfitting.srt	18.2 KB
	013.Solving the Problem of Overfitting/041. Cost Function.mp4	15.5 MB
	013.Solving the Problem of Overfitting/041. Cost Function.srt	18.6 KB
	013.Solving the Problem of Overfitting/042. Regularized Linear Regression.mp4	15.6 MB
	013.Solving the Problem of Overfitting/042. Regularized Linear Regression.srt	14.2 KB
	013.Solving the Problem of Overfitting/043. Regularized Logistic Regression.mp4	16.8 MB
	013.Solving the Problem of Overfitting/043. Regularized Logistic Regression.srt	16.2 KB
	014.Motivations/044. Non-linear Hypotheses.mp4	14.7 MB
	014.Motivations/044. Non-linear Hypotheses.srt	18 KB
	014.Motivations/045. Neurons and the Brain.mp4	14.6 MB
	014.Motivations/045. Neurons and the Brain.srt	15.5 KB
	015.Neural Networks/046. Model Representation I.mp4	18 MB
	015.Neural Networks/046. Model Representation I.srt	14.4 KB
	015.Neural Networks/047. Model Representation II.mp4	18.4 MB
	015.Neural Networks/047. Model Representation II.srt	21.1 KB
	016.Applications/048. Examples and Intuitions I.mp4	10.1 MB
	016.Applications/048. Examples and Intuitions I.srt	8.5 KB
	016.Applications/049. Examples and Intuitions II.mp4	20.9 MB
	016.Applications/049. Examples and Intuitions II.srt	11.4 KB
	016.Applications/050. Multiclass Classification.mp4	7 MB

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