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This is a code repository for the upcoming book "Java Deep Learning cookbook" sponsored by Packt Publishing. We use and promote deeplearning4j library for all use-cases in this book. Official deeplearning4j version targeted in this cookbook is 1.0.0-beta3. For the same reason, some of the methods or approaches discussed in this cookbook may get deprecated in their newer versions. So, be sure to refer their latest API documentation. You may use newer versions that has bug fixes and new features.

Update

Java deep learning cookbook is released on November 8, 2019.

Each chapter will have separate source folder where all examples are stored for the particular chapter. For example, if you want to import the code for chapter 2, navigate to the chapter directory first and then import the directory sourceCode/cookbook-app in your IDE. You should also see pom.xml located there.

• Navigate to the sourceCode root directory.
• Open as a Maven project and compile.

mvn clean install

If you face issues with Intellij being not able to detect dependencies or any workspace issues, try running the below command:

mvn idea:idea

Delete workspace.xml under .idea directory if problem persists.

1. Introduction to Deep Learning in Java
2. Data Extraction, Transform and Loading
3. Building Deep Neural Networks for Binary classification
4. Building Convolutional Neural Networks
5. Implementing NLP
6. Constructing LTSM Network for time series
7. Constructing LTSM Neural network for sequence classification
8. Performing Anomaly detection on unsupervised data
9. Using RL4J for Reinforcement learning
10. Developing applications in distributed environment
11. Applying Transfer Learning to network models
12. Benchmarking and Neural Network Optimization