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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 FREE CHAPTER 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

Executing a transform process

After the transformation process has been defined, we can execute it in a controlled pipeline. It can be executed using batch processing, or we can distribute the effort to a Spark cluster. Previously, we look at TransformProcessRecordReader, which automatically does the transformation in the background. We cannot feed and execute the data if the dataset is huge. Effort can be distributed to a Spark cluster for a larger dataset. You can also perform regular local execution. In this recipe, we will discuss how to execute a transform process locally as well as remotely.

How to do it...

  1. Load the dataset into RecordReader. Load the CSV data in the case of CSVRecordReader:
RecordReader reader = new...
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