Machine Learning Using Python. A Guide for Data Professionals
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This book is an excellent source of information for everyone who is going to use machine learning in practice. Now, machine learning has become an integral part of various commercial and research projects, and one should not think that this area is the prerogative of exclusively large companies with powerful teams of analysts.
This book will teach you the practical ways to build MO systems, even if you are still a beginner in this area. It explains in detail all the stages necessary for creating a successful machine learning project using the Python and Library of Scikit-Learn, Numpy and MatPlotlib. The authors focused their attention solely on practical aspects of the use of machine learning algorithms, leaving their mathematical justification outside the book. This book is addressed to specialists who solve real tasks, and since the scope of the methods of MO is almost limitless by reading this book, you can build the current machine learning system in any scientific or commercial field on your own
This book will teach you the practical ways to build MO systems, even if you are still a beginner in this area. It explains in detail all the stages necessary for creating a successful machine learning project using the Python and Library of Scikit-Learn, Numpy and MatPlotlib. The authors focused their attention solely on practical aspects of the use of machine learning algorithms, leaving their mathematical justification outside the book. This book is addressed to specialists who solve real tasks, and since the scope of the methods of MO is almost limitless by reading this book, you can build the current machine learning system in any scientific or commercial field on your own
Author:
Author:Мюллер Андреас, Гвидо Сара
Cover:
Cover:Soft
Category:
- Category:Arts & Photography
- Category:Computer & Technology
- Category:Engineering & Transportation
- Category:Medical Books
- Category:Agriculture
Publication language:
Publication Language:Russian
Paper:
Paper:Offset
ISBN:
ISBN:978-5-907515-03-1
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