000 -LEADER |
fixed length control field |
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220627b xxu||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781108494939 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.32 |
Item number |
MEH |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Mehlig, Bernhard |
245 ## - TITLE STATEMENT |
Title |
Machine learning with neural networks : an introduction for scientists and engineers |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Name of publisher, distributor, etc |
Cambridge University Press, |
Date of publication, distribution, etc |
2022 |
Place of publication, distribution, etc |
Cambridge : |
300 ## - PHYSICAL DESCRIPTION |
Extent |
ix, 249 p. ; |
Other physical details |
ill., |
Dimensions |
26 cm |
365 ## - TRADE PRICE |
Price amount |
39.99 |
Price type code |
GBP |
Unit of pricing |
100.50 |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index. |
520 ## - SUMMARY, ETC. |
Summary, etc |
This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning |
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Topical term or geographic name as entry element |
Neural networks |
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Topical term or geographic name as entry element |
Computer science |
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Topical term or geographic name as entry element |
Activation Function |
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Backpropagation |
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Central-limit theorem |
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Cross-talk term |
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Decision boundary |
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Topical term or geographic name as entry element |
Energy function |
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Topical term or geographic name as entry element |
Feed-forward network |
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Topical term or geographic name as entry element |
Hidden neuron |
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Topical term or geographic name as entry element |
Hopfield network |
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Topical term or geographic name as entry element |
Image Net |
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Topical term or geographic name as entry element |
Markov chain |
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Topical term or geographic name as entry element |
Mean-field theory |
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Topical term or geographic name as entry element |
Noise level |
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Topical term or geographic name as entry element |
Output neuron |
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Principle component |
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Topical term or geographic name as entry element |
Q-table |
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Topical term or geographic name as entry element |
Residwal network |
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Topical term or geographic name as entry element |
Stochastic gradient descent |
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Topical term or geographic name as entry element |
Vanishing gradient |
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Topical term or geographic name as entry element |
Winning neoron |
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Topical term or geographic name as entry element |
XOR problem |
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Topical term or geographic name as entry element |
Boltzmann Machines |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
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Item type |
Books |