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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

This chapter's source code can be located here: https://github.com/PacktPublishing/Java-Deep-Learning-Cookbook/tree/master/11_Applying_Transfer_Learning_to_network_models/sourceCode/cookbookapp/src/main/java.

After cloning the GitHub repository, navigate to the Java-Deep-Learning-Cookbook/11_Applying_Transfer_Learning_to_network_models/sourceCode directory, then import the cookbookapp project as a Maven project by importing pom.xml.

You need to have the pre-trained model from Chapter 3, Building Deep Neural Networks for Binary Classification, to run the transfer learning example. The model file should be saved in your local system once the Chapter 3, Building Deep Neural Networks for Binary Classification source code is executed. You need to load the model here while executing the source code in this chapter. Also, for the SaveFeaturizedDataExample...
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