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Java deep learning cookbook : train neural networks for classification, NLP, and reinforcement learning using deeplearning4j /
Deep Learning is a trending topic in AI currently, as it allows you to make faster and more accurate predictions using the power of neural networks. This book will teach you the process of neural network design, and show you how to develop efficient deep learning applications using Deeplearning4j th...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2019.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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|---|---|---|---|
| 001 | EBSCO_on1127946188 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 020 | |a 1788999479 | ||
| 020 | |a 9781788999472 |q (electronic bk.) | ||
| 029 | 1 | |a AU@ |b 000071825024 | |
| 035 | |a (OCoLC)1127946188 | ||
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| 100 | 1 | |a Raj, Rahul, |e author | |
| 245 | 1 | 0 | |a Java deep learning cookbook : |b train neural networks for classification, NLP, and reinforcement learning using deeplearning4j / |c Rahul Raj. |
| 260 | |a Birmingham : |b Packt Publishing, Limited, |c 2019. | ||
| 300 | |a 1 online resource (294 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 520 | |a Deep Learning is a trending topic in AI currently, as it allows you to make faster and more accurate predictions using the power of neural networks. This book will teach you the process of neural network design, and show you how to develop efficient deep learning applications using Deeplearning4j through practical and easy to implement recipes. | ||
| 500 | |a Includes index. | ||
| 505 | 0 | |a Java deep learning cookbook: train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j -- Dedication -- About Packt -- Contributors -- Table of Contents -- Preface -- 1. Introduction to Deep Learning in Java -- 2. Data Extraction, Transformation, and Loading -- 3. Building Deep Neural Networks for Binary Classification -- 4. Building Convolutional Neural Networks -- 5. Implementing Natural Language Processing -- 6. Constructing an LSTM Network for Time Series -- 7. Constructing an LSTM Neural Network for Sequence Classification -- 8. Performing Anomaly Detection on Unsupervised Data -- 9. Using RL4J for Reinforcement Learning -- 10. Developing Applications in a Distributed Environment -- 11. Applying Transfer Learning to Network Models -- 12. Benchmarking and Neural Network Optimization -- Other Books You May Enjoy -- Index. | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Java (Computer program language) | |
| 650 | 0 | |a Natural language processing (Computer science) | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Java (Langage de programmation) | |
| 650 | 6 | |a Traitement automatique des langues naturelles. | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a Neural networks & fuzzy systems. |2 bicssc | |
| 650 | 7 | |a Natural language & machine translation. |2 bicssc | |
| 650 | 7 | |a Computers |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Computers |x Neural Networks. |2 bisacsh | |
| 650 | 7 | |a Computers |x Natural Language Processing. |2 bisacsh | |
| 650 | 7 | |a Java (Computer program language) |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Natural language processing (Computer science) |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Raj, Rahul. |t Java Deep Learning Cookbook : Train Neural Networks for Classification, NLP, and Reinforcement Learning Using Deeplearning4j. |d Birmingham : Packt Publishing, Limited, ©2019 |z 9781788995207 |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2293855 |z Texto completo |
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| 938 | |a EBSCOhost |b EBSC |n 2293855 | ||
| 994 | |a 92 |b IZTAP | ||