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Hands-on machine learning with Sciki...

Geron, Aurelien.

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Hands-on machine learning with Scikit-Learn and TensorFlow :/ Aurelien Geron.
Reminder of title:	concepts, tools, and techniques to build intelligent systems /
Author:	Geron, Aurelien.
Published:	Beijing ;O'Reilly Media, : c2017.,
[NT 15000922]:	1st ed.
Description:	xx, 551 p. :ill. ; : 24 cm.;
基督教聖經之智慧書導讀 :	"Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started" --
Subject:	Machine learning. -
ISBN:	1491962291 (pbk.)

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /
Geron, Aurelien.

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /Aurelien Geron. - 1st ed. - Beijing ;O'Reilly Media,c2017. - xx, 551 p. :ill. ;24 cm.

Includes bibliographical references and index.

"Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started" --

ISBN: 1491962291 (pbk.)

LCCN: 2018418542Subjects--Topical Terms:

248498
Machine learning.

LC Class. No.: Q325.5 / .G47 2017

Dewey Class. No.: 006.31

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /
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010 $a 2018418542
020 $a 1491962291 (pbk.)
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050 0 0 $a Q325.5 $b .G47 2017
082 0 4 $a 006.31 $2 23
087 $a 312.9831 $b G377 2017
100 1 $a Geron, Aurelien. $3 447735
245 1 0 $a Hands-on machine learning with Scikit-Learn and TensorFlow : $b concepts, tools, and techniques to build intelligent systems / $c Aurelien Geron.
250 $a 1st ed.
260 # $a Beijing ; $a Boston : $b O'Reilly Media, $c c2017.
300 $a xx, 551 p. : $b ill. ; $c 24 cm.
504 $a Includes bibliographical references and index.
520 # $a "Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started" -- $c Back cover.
650 # 0 $2 96060 $a Machine learning. $3 248498
650 # 0 $2 96060 $a Artificial intelligence. $3 233060