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Java Deep Learning Cookbook

You're reading from   Java Deep Learning Cookbook Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781788995207
Length 304 pages
Edition 1st Edition
Languages
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Author (1):
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Rahul Raj Rahul Raj
Author Profile Icon Rahul Raj
Rahul Raj
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Deep Learning in Java 2. Data Extraction, Transformation, and Loading FREE CHAPTER 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 13. Other Books You May Enjoy

Who this book is for

In order to get the most out of this book, we recommend that readers have basic knowledge of deep learning and data analytics. It is also preferable for readers to have basic knowledge of MLP (multilayer perceptrons) or feed forward networks, recurrent neural networks, LSTM, word vector representations, and some level of debugging skills to interpret the errors from the error stack. As this book targets Java and the DL4J library, readers should also have sound knowledge of Java and DL4J. This book is not suitable for anyone who is new to programming or who doesn't have basic knowledge of deep learning.

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