MARC details
| 000 -LIDER |
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| fixed length control field |
03478nam a22004575i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-3-319-94463-0 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240111132923.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
180825s2018 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783319944630 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q334-342 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
COM004000 |
| Source |
bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Aggarwal, Charu C. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Neural Networks and Deep Learning |
| Medium |
[electronic resource] : |
| Remainder of title |
A Textbook / |
| Statement of responsibility, etc. |
by Charu C. Aggarwal. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. 2018. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XXIII, 497 p. 139 illus., 11 illus. in color. |
| Other physical details |
online resource. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Acceso multiusuario |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1 An Introduction to Neural Networks -- 2 Machine Learning with Shallow Neural Networks -- 3 Training Deep Neural Networks -- 4 Teaching Deep Learners to Generalize -- 5 Radical Basis Function Networks -- 6 Restricted Boltzmann Machines -- 7 Recurrent Neural Networks -- 8 Convolutional Neural Networks -- 9 Deep Reinforcement Learning -- 10 Advanced Topics in Deep Learning. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques. |
| 541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Owner |
UABC ; |
| Method of acquisition |
Temporal ; |
| Date of acquisition |
01/01/2021-12/31/2023. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Computers. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Microprocessors. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Information Systems and Communication Service. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Processor Architectures. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9783319944623 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9783319944647 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9783030068561 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Public note |
Libro electrónico |
| Uniform Resource Identifier |
http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-94463-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Libro Electrónico |
