MARC details
| 000 -LEADER |
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| fixed length control field |
02396nam a2200241Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250520103029.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250520s9999 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781098125974 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
Q 325.5 .G47 2023 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Géron, Aurélien |
| Relator term |
author |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Hands-on machine learning with scikit-learn, teras, and tensorflow : |
| Remainder of title |
concepts, tools, and techniques to build intelligent systems / |
| Statement of responsibility, etc. |
Aurélien Géron |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Third Edition |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Sebastopol, California : |
| Name of publisher, distributor, etc. |
O'Reilly Media, Incorporated, |
| Date of publication, distribution, etc. |
c2023 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 834 pages : |
| Other physical details |
color illustrations ; |
| Dimensions |
24 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
USD38 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
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 -- 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 -- Autoencoders, GANs, and diffusion models -- Reinforcement learning -- Training and deploying TensorFlow models at scale. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Through a recent series of 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 best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
ARTIFICIAL INTELLIGENCE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Books |
