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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

Building a transformation process

The next step after schema creation is to define a data transformation process by adding all the required transformations. We can manage an ordered list of transformations using TransformProcess. During the schema creation process, we only defined a structure for the data with all its existing features and didn't really perform transformation. Let's look at how we can transform the features in the datasets from a non-numeric format into a numeric format. Neural networks cannot understand raw data unless it is mapped to numeric vectors. In this recipe, we will build a transformation process from the given schema.

How to do it...

  1. Add a list of transformations to TransformProcess....
You have been reading a chapter from
Java Deep Learning Cookbook
Published in: Nov 2019
Publisher: Packt
ISBN-13: 9781788995207
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