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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

Importing and loading Keras models and layers

There can be times when you want to import a model that is not available in the DL4J Model Zoo API. You might have created your own model in Keras/TensorFlow, or you might be using a pre-trained model from Keras/TensorFlow. Either way, we can still load models from Keras/TensorFlow using the DL4J model import API.

Getting ready

This recipe assumes that you already have the Keras model (pre-trained/not pre-trained) set up and ready to be imported to DL4J. We will skip the details about how to save Keras models to disk as it is beyond the scope of this book. Usually, Keras models are stored in .h5 format, but that isn't a restriction as the model-import API can import from...

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