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Introduction to machine learning wit...

Guido, Sarah,

Introduction to machine learning with Python :a guide for data scientists /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Introduction to machine learning with Python :Andreas C. Müller and Sarah Guido.
其他題名:	a guide for data scientists /
其他題名:	Machine learning with Python
作者:	Müller, Andreas C.,
其他作者:	Guido, Sarah,
出版者:	Sebastopol, CA :O'Reilly Media, Inc.,2016.
面頁冊數:	xii, 384 p. :ill. ;24 cm.
附註:	Includes index.
標題:	Data mining.
ISBN:	9781449369415 (pbk.) :

Introduction to machine learning with Python :a guide for data scientists /
Müller, Andreas C.,

Introduction to machine learning with Python :a guide for data scientists /Machine learning with PythonAndreas C. Müller and Sarah Guido. - 1st ed. - Sebastopol, CA :O'Reilly Media, Inc.,2016. - xii, 384 p. :ill. ;24 cm.

Includes index.

Introduction -- Supervised learning -- Unsupervised learning and preprocessing -- Representing data and engineering features -- Modelevaluation and improvement -- Algorithm chains and pipelines -- Working withtext data -- Wrapping up.

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to largecompanies with extensive research teams. If you use Python, even as abeginner, this book will teach you practical ways to build your own machinelearning solutions. With all the data available today, machine learningapplications are limited only by your imagination. You'll learn the stepsnecessary to create a successful machine-learning application with Pythonand the scikit-learn library. Authors Andreas Müller and Sarah Guido focuson the practical aspects of using machine learning algorithms, rather thanthe math behind them. Familiarity with the NumPy and matplotlib librarieswill help you get even more from this book. --

ISBN: 9781449369415 (pbk.) :NT$1583

LCCN: 2017394288Subjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.73.P98 / M85 2016

Dewey Class. No.: 005.133

Introduction to machine learning with Python :a guide for data scientists /
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520 $a Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to largecompanies with extensive research teams. If you use Python, even as abeginner, this book will teach you practical ways to build your own machinelearning solutions. With all the data available today, machine learningapplications are limited only by your imagination. You'll learn the stepsnecessary to create a successful machine-learning application with Pythonand the scikit-learn library. Authors Andreas Müller and Sarah Guido focuson the practical aspects of using machine learning algorithms, rather thanthe math behind them. Familiarity with the NumPy and matplotlib librarieswill help you get even more from this book. -- $c Provided by publisher.
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