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Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : (Record no. 142504)

MARC details
000 -LEADER
fixed length control field 02230nam a22002537a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260911111806.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260911s2023 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781098125974
040 ## - CATALOGING SOURCE
Transcribing agency PK-LaUMT
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number T 006.31
Item number GER-H
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 Aurélien Géron
250 ## - EDITION STATEMENT
Edition statement 3rd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Sebatopol :
Name of publisher, distributor, etc O'Reilly Media, Inc.,
Date of publication, distribution, etc 2023
300 ## - PHYSICAL DESCRIPTION
Extent xxv, 834 p.
500 ## - GENERAL NOTE
General note Index present
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 bestselling 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 Aurélien Géron 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: Use Scikit-learn to track an example ML project end to end; Explore several models, including support vector machines, decision trees, random forests, and ensemble methods; Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection; Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers; Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning" --Back cover
546 ## - LANGUAGE NOTE
Language note Eng
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python (Computer program language)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element TensorFlow
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Home library Current library Date acquired Full call number Barcode Date last seen Price effective from Koha item type Copy number
      UMT Main Campus UMT Main Campus 2026-09-11 006.31 GER-H 154347 2026-09-11 2026-09-11 Books  
      UMT Main Campus UMT Main Campus 2026-09-11 006.31 GER-H 154348 2026-09-11 2026-09-11 Books C.2
      UMT Main Campus UMT Main Campus 2026-09-11 006.31 GER-H 154349 2026-09-11 2026-09-11 Books C.3
      UMT Main Campus UMT Main Campus 2026-09-11 006.31 GER-H 154350 2026-09-11 2026-09-11 Books C.4
      UMT Main Campus UMT Main Campus 2026-09-11 006.31 GER-H 154351 2026-09-11 2026-09-11 Books C.5