Java Deep Learning Cookbook

Java Deep Learning Cookbook starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. (Limited-time offer)

Table of Contents

• 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

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