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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 Introduction to Deep Learning in Java Data Extraction, Transformation, and Loading Building Deep Neural Networks for Binary Classification Building Convolutional Neural Networks Implementing Natural Language Processing Constructing an LSTM Network for Time Series Constructing an LSTM Neural Network for Sequence Classification Performing Anomaly Detection on Unsupervised Data Using RL4J for Reinforcement Learning Developing Applications in a Distributed Environment Applying Transfer Learning to Network Models Benchmarking and Neural Network Optimization Other Books You May Enjoy

Training images and evaluating CNN output

We have layer configurations in place. Now, we need to train the CNN to make it suitable for predictions. In a CNN, filter values will be adjusted during the training process. The network will learn by itself how to choose proper filters (feature maps) to produce the best results. We will also see that the efficiency and performance of the CNN becomes a challenging task because of the complexity involved in computation. In this recipe, we will train and evaluate our CNN model.

How to do it...

  1. Load and initialize the training data using ImageRecordReader:
ImageRecordReader imageRecordReader = new ImageRecordReader(imageHeight,imageWidth,channels,parentPathLabelGenerator);
imageRecordReader...
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