Deep Learning : Foundations and Concepts (Record no. 51007)

MARC details
000 -LEADER
fixed length control field 01892 a2200193 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250804173954.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031454677
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.32 BIS
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bishop, Christopher M.
245 ## - TITLE STATEMENT
Title Deep Learning : Foundations and Concepts
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer
Date of publication, distribution, etc 2024
Place of publication, distribution, etc Switzerland
300 ## - PHYSICAL DESCRIPTION
Extent 649
520 ## - SUMMARY, ETC.
Summary, etc This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.<br/><br/>The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study.<br/><br/>A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Deep Learning
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 Computer Software
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Bishop, Hugh
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification

No items available.