Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow : (Record no. 1389)

MARC details
000 -LEADER
fixed length control field 03366cam a2200289Ii 4500
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field ta
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200219s2019 caua 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781492032649
Qualifying information (softcover)
International Standard Book Number 1492032646
Qualifying information (softcover)
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1124925244
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .G476 2019
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Geron, Aurelien.
245 10 - TITLE STATEMENT
Title Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow :
Remainder of title concepts, tools, and techniques to build intelligent systems /
Statement of responsibility, etc. Aurelien Geron.
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Sebastopol, CA :
Name of publisher, distributor, etc. O'Reilly Media, Inc.,
Date of publication, distribution, etc. 2019.
300 ## - PHYSICAL DESCRIPTION
Extent xxv, 819 p. :
Other physical details col. ill.
500 ## - GENERAL NOTE
General note Includes index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Part I The fundamentals of machine learning. The machine learning landscape -- End-to-end machine learning project -- Classification -- Training models ; Support vector machines -- Decision trees -- Ensemble learning and random forests -- Dimensionality reduction -- Unsupervised learning techniques -- Part II Neural networks and deep learning. Introduction to artificial neural networks with Keras -- Training deep neural networks -- Custom models and training with TensorFlow -- Loading and preprocessing data with TensorFlow -- Deep computer vision using convolutional neural networks -- Processing sequences using RNNs and CNNs -- Natural language processing with RNNs and attention -- Representation learning and generative learning using autoencoders and GANs -- Reinforcement learning -- Training and deploying TensorFlow models at scale.
520 ## - SUMMARY, ETC.
Summary, etc. 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. The updated edition of this best-selling book uses concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow 2-to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Practitioners will learn a range of techniques that they can quickly put to use on the job. Part 1 employs Scikit-Learn to introduce fundamental machine learning tasks, such as simple linear regression. Part 2, which has been significantly updated, employs Keras and TensorFlow 2 to guide the reader through more advanced machine learning methods using 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. NEW FOR THE SECOND EDITION:Updated all code to TensorFlow 2Introduced the high-level Keras APINew and expanded coverage including TensorFlow's Data API, Eager Execution, Estimators API, deploying on Google Cloud ML, handling time series, embeddings and more With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released.
630 04 - SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title TensorFlow.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
Topical term or geographic name entry element Artificial intelligence.
Topical term or geographic name entry element Python (Computer program language)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Full call number Barcode Date last seen Price effective from Koha item type
        Punsarn Library Punsarn Library General Stacks 17/06/2021 Q325.5 .G476 2019 PNLIB21061203 17/06/2021 17/06/2021 Books