MACHINE LEARNING WITH PYTHON. SUPERVISED LEARNING TECHNIQUES: REGRESSION
by J. BROWN 2020-05-26 04:22:12
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In this book, supervised learning techniques related to regression will be developed. More specifically, we will go deeper into the linear models, LASSO regression, LARS LASSO regression, RIDGE Regression, Least Angle Regression, Multitask LASSO regr... Read more
In this book, supervised learning techniques related to regression will be developed. More specifically, we will go deeper into the linear models, LASSO regression, LARS LASSO regression, RIDGE Regression, Least Angle Regression, Multitask LASSO regression, Elastic Net Regression, Multi task Elastic Net Regression, SGD Regression, Support Vector Regression SVR, Robust Regression, Huber Regression, Kernel regression, RANSAC Regression and other supervised techniques based in Regression. Variety of examples are solved from the Python Scikit Learn library. Less
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  • Print pages
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  • Publication date
  • ISBN
  • 6.00(w)x9.00(h)x0.48
  • 208
  • Independently published
  • April 29, 2020
  • 9798641604923
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