MARC details
| 000 -LEADER |
| fixed length control field |
02402nam a2200289Ia 4500 |
| 001 - CONTROL NUMBER |
| control field |
10921 |
| 003 - CONTROL NUMBER IDENTIFIER |
| control field |
MX-MdCICY |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
| control field |
20241009165145.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
| fixed length control field |
220110s2021 nyua 001 0 ENG d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
| International Standard Book Number |
1617296864 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
| International Standard Book Number |
9781617296864 |
| 040 ## - CATALOGING SOURCE |
| Transcribing agency |
UKMGB |
| Modifying agency |
GUA |
| Description conventions |
rda |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
| Classification number |
006.31 |
| Item number |
C56 2021 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
| Personal name |
Chollet, Francois |
| 245 10 - TITLE STATEMENT |
| Title |
Deep learning with Python / |
| Statement of responsibility, etc. |
Francois Chollet |
| 250 ## - EDITION STATEMENT |
| Edition statement |
2 ed. |
| 264 31 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Place of production, publication, distribution, manufacture |
Shelter Island, NY : |
| Name of producer, publisher, distributor, manufacturer |
Mamming Publications Co., |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2021 |
| 300 ## - PHYSICAL DESCRIPTION |
| Extent |
xxiii, 478 p. : |
| Other physical details |
il.; |
| Dimensions |
24 cm. |
| 500 ## - GENERAL NOTE |
| General note |
Previous edition: 2018. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
| Bibliography, etc. note |
Incluye índice |
| 505 0# - FORMATTED CONTENTS NOTE |
| Formatted contents note |
Contenido: 1. What is deep learning? -- 2. The mathematical building blocks of neural networks -- 3. Introduction to Keras and TensorFlow -- 4. Getting started with neural networks: classification and regression -- 5. Fundamentals of machine learning -- 6. The universal workflow of machine learning -- 7. Working with Keras: a deep dive -- 8. Introduction to deep learning for computer vision -- 9. Advanced deep learning for computer vision -- 10. Deep learning for timeseries -- 11. Deep learning for text -- 12. Generative deep learning -- 13. Best practices for the real world -- 14. Conclusions. |
| 520 ## - SUMMARY, ETC. |
| Summary, etc. |
Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-- even if you have no background in mathematics or data science. This book shows you how to get started. "Deep learning with Python, second edition" introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator Francois Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, youll build your understanding through intuitive explanations, crisp illustrations, and clear examples. Youll quickly pick up the skills you need to start developing deep-learning applications.-- |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
PYTHON |
| General subdivision |
PROGRAMAS PARA COMPUTADORA |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
REDES NEURONALES |
| General subdivision |
APLICACIONES CIENTIFICAS |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
| Uniform Resource Identifier |
<a href="https://www.cicy.mx/sitios/sib/doctoelectronico/10921.pdf">https://www.cicy.mx/sitios/sib/doctoelectronico/10921.pdf</a> |
| Public note |
Ver tabla de contenido y/o resumen |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Libros impresos |