Artificial Neural Networks with Java

Part One. Getting Started with Neural Networks Chapter 1. Learning Neural Network
Biological and Artificial Neurons Activation Functions Summary
Chapter 2. Internal Mechanism of Neural Network Processing
Function to be Approximated Network Architecture Forward Pass Calculations Back-Propagation Pass Calculations Function derivative and function divergent Table of Most Commonly Used Function Derivatives Summary

Chapter 3. Manual Neural Network Processing
Example 1. Manual Approximation of a Function at a Single Point Building the Neural Network Forward pass calculation Backward Pass Calculation Calculating Weight Adjustments for the Output Layer Neurons Calculating Weight Adjustments for the Hidden Layer Neurons Updating Network Biases Back to the Forward Pass Matrix Form of Network Calculation Digging Deeper Mini-Batches and Stochastic Gradient Summary

Part Two. Neural Network Java Development Environment Chapter 4. Configuring Your Development Environment
Installing Java 8 Environment on Your Windows Machine Installing NetBeans IDE Installing Encog Java Framework Installing XChart Package Summary
Chapter 5. Neural Network Development Using Java Encog Framework
Example 2. Function Approximation using Java environment Network Architecture Normalizing the Input datasets Building the Java Program that Normalizes Both Datasets Program Code Debugging and Executing the Program Processing Results for the Training Method Testing the Network Testing Results Digging deeper. Summary
Part Three. Development Non-Trivial Neural Network Applications Chapter 6. Neural Network Prediction Outside of the Training Range Example 3a. Approximating Periodic Functions Outside of the Training Range Network Architecture for Example 3a Program Code for Example 3a Testing The Network Example 3b. Correct Way of Approximating Periodic Functions Outside of the Training Range Preparing the Training Data Network Architecture for the Example 3b Program Code for

Igor Livshin is a senior architect with extensive experience in developing large-scale applications. He worked for many years for two large insurance companies: CNN and Blue Cross & Blue Shield of Illinois. He currently works as a senior researcher at DevTechnologies specializing in AI and neural networks. Igor has a master's degree in computer science from the Institute of Technology in Odessa, Russia/Ukraine.