This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification and Neuronal Networks Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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This post - like all others in this series - refers to Andrew Ng's machine learning class on Coursera and provides Python code for the  exercises.  The pure code, exercise text, and data files for all parts of the series are available here. Part 1:  Linear Regression with One Variable Part 2 :  Linear Regression with Multiple Variables Part 3 : Logistic Regression Part 4:  Multi-class Classification Part 5:  Neuronal Network Learning Part 6 : Regularized Linear Regression and Bias Variance  Part 7: Support Vector Machines Part 8: Dimensionality…

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