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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

Technical requirements

The source code for this chapter can be found here:
https://github.com/PacktPublishing/Java-Deep-Learning-Cookbook/blob/master/09_Using_RL4J_for_Reinforcement%20learning/sourceCode/cookbookapp/src/main/java/MalmoExample.java.

After cloning our GitHub repository, navigate to the Java-Deep-Learning-Cookbook/09_Using_RL4J_for_Reinforcement learning/sourceCode directory. Then, import the cookbookapp project as a Maven project by importing pom.xml.

You need to set up a Malmo client to run the source code. First, download the latest Project Malmo release as per your OS (https://github.com/Microsoft/malmo/releases):

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