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The Machine Learning Workshop

You're reading from   The Machine Learning Workshop Get ready to develop your own high-performance machine learning algorithms with scikit-learn

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219061
Length 286 pages
Edition 2nd Edition
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Author (1):
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Hyatt Saleh Hyatt Saleh
Author Profile Icon Hyatt Saleh
Hyatt Saleh
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Scikit-Learn

Created in 2007 by David Cournapeau as part of a Google Summer of Code project, scikit-learn is an open source Python library made to facilitate the process of building models based on built-in ML and statistical algorithms, without the need for hardcoding. The main reasons for its popular use are its complete documentation, its easy-to-use API, and the many collaborators who work every day to improve the library.

Note

You can find the documentation for scikit-learn at http://scikit-learn.org.

Scikit-learn is mainly used to model data, and not as much to manipulate or summarize data. It offers its users an easy-to-use, uniform API to apply different models with little learning effort, and no real knowledge of the math behind it is required.

Note

Some of the math topics that you need to know about to understand the models are linear algebra, probability theory, and multivariate calculus. For more information on these models, visit https://towardsdatascience...

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