Java Deep Learning Cookbook

Table of Contents

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