Neural Network Programming with Java > PACKT 원서리스트

1: Getting Started with Neural Networks
Discovering neural networks
Why artificial neural network?
How neural networks are arranged
Learning about neural network architectures
From ignorance to knowledge – learning process
Let the implementations begin! Neural networks in practice
Summary

2: How Neural Networks Learn
Learning ability in neural networks
Learning paradigms
Systematic structuring – learning algorithm
Examples of learning algorithms
Coding of the neural network learning
Two practical examples
Summary

3: Handling Perceptrons
Studying the perceptron neural network
Popular multilayer perceptrons (MLPs)
Interesting MLP applications
Learning process in MLPs
Hands-on MLP implementation!
Levenberg–Marquardt implementation
Practical application – types of university enrolments
Summary

4: Self-Organizing Maps
Neural networks' unsupervised way of learning
Some unsupervised learning algorithms
Kohonen self-organizing maps (SOMs)
Coding of the Kohonen algorithm
Summary

5: Forecasting Weather
Neural networks for prediction problems
No data, no neural net – selecting data
Adjusting values – data preprocessing
Java implementation for weather prediction
Empirical design of neural networks
Summary

6: Classifying Disease Diagnosis
What are classification problems, and how can neural networks be applied to them?
A special type of activation function – Logistic regression
Applying neural networks for classification
Disease diagnosis with neural networks
Summary

7: Clustering Customer Profiles
Clustering task
Applied unsupervised learning
Customer profiling
Implementation in Java
Summary

8: Pattern Recognition (OCR Case)
What is pattern recognition all about?
How to apply neural networks in pattern recognition
The OCR problem
Let the coding begin!
Summary

9: Neural Network Optimization and Adaptation
Common issues in neural network implementations
Input selection
Structure selection
Online retraining
Adaptive neural networks
Summary
appA: Appendix A: Setting up the NetBeans Environment
Download and install NetBeans
Setting up the NetBeans environment
Importing a project
Programming and running code with NetBeans
Debugging with NetBeans
appB: Appendix B: Setting Up the Eclipse Environment
Download and install Eclipse
Setting up the Eclipse environment
Importing a project
Programming and running code with the Eclipse IDE
Debugging with the Eclipse IDE
appC: Appendix C: References

Chapter 1 - Getting Started with Neural Networks
Chapter 2 - How Neural Networks Learn
Chapter 3 - Working with Perceptrons
Chapter 4 - Self-Organizing Maps
Chapter 5 - Forecasting Weather
Chapter 6 - Disease Diagnosis
Chapter 7 - Clustering Customer Profiles
Chapter 8 - Pattern Recognition (the OCR Case)
Chapter 9 - Neural Network Optimization and Adaptation
backindex: Appendix D: Index