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...
I tiakina i:
| Ngā kaituhi matua: | , |
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| Hōputu: | Pukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
Sebastopol, CA, USA :
O'Reilly Media, Inc.,
2016. ©2017
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| Putanga: | First edition. |
| Ngā marau: | |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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| Whakarāpopototanga: | 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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| Whakaahutanga tūemi: | Includes index. |
| Whakaahuatanga ōkiko: | xii, 376 páginas : illustrations |
| ISBN: | 9781449369415 1449369413 |