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Java Deep Learning Cookbook

You're reading from  Java Deep Learning Cookbook

Product type Book
Published in Nov 2019
Publisher Packt
ISBN-13 9781788995207
Pages 304 pages
Edition 1st Edition
Languages
Author (1):
Rahul Raj Rahul Raj
Profile icon Rahul Raj

Table of Contents (14) Chapters

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 13. Other Books You May Enjoy

Technical requirements

A concrete implementation of the use case discussed in this chapter can be found here: https://github.com/PacktPublishing/Java-Deep-Learning-Cookbook/blob/master/06_Constructing_LSTM_Network_for_time_series/sourceCode/cookbookapp-lstm-time-series/src/main/java/LstmTimeSeriesExample.java.

After cloning the GitHub repository, navigate to the Java-Deep-Learning-Cookbook/06_Constructing_LSTM_Network_for_time_series/sourceCode directory. Then, import the cookbookapp-lstm-time-series project as a Maven project by importing pom.xml.

Download the clinical time series data from here: https://skymindacademy.blob.core.windows.net/physionet2012/physionet2012.tar.gz. The dataset is from the PhysioNet Cardiology Challenge 2012.

Unzip the package after the download. You should see the following directory structure:

The features are contained in a directory called sequence...

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