Introduction to machine learning with Python : a guide for data scientists /
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solu...
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| Auteurs principaux: | , |
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| Format: | Livre |
| Langue: | anglais |
| Publié: |
Sebastopol, CA, USA :
O'Reilly Media, Inc.,
2016. ©2017
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| Édition: | First edition. |
| Sujets: | |
| Tags: |
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| Résumé: | Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. -- |
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| Description: | Includes index. |
| Description matérielle: | xii, 376 páginas : illustrations |
| ISBN: | 9781449369415 1449369413 |