Introduction to Neural Networks

This free online book is divided into the following sections: Introduction, Components, Supervised Learning, Unsupervised Learning and Applications.


It has been said that the human nervous system is the most complex and versatile achievement of evolution. It mediates everything from the simple knee-jerk reflex to the so-called higher cognitive functions of learning and memory. The structure of the nervous system provides important clues as to how it achieves these feats. Unlike computers that operate primarily sequentially (processing tasks one at a time), the nervous system is massively parallel (processing many tasks at the same time). In fact, the human nervous system contains about a hundred billion processors termed neurones each of which is connected to thousands of its neighbours. It was the observation of these interconnected neurones that gave rise to the name neural networks.

Artificial neural networks grew out of research into artificial intelligence and were designed to mimic the biological neural networks found in the brain. They are formed from groups of artificial neurones connected together in much the same way as the brains neurones. Artificial neural networks offer advantages over conventional computing in fields such as pattern recognition, generalisation and trend prediction.

Table of Contents

  • Introduction
  • Components
  • Supervised Learning
  • Unsupervised Learning
  • Applications
  • Conclusion

Book Details

Author(s): Neural Network Solutions
Format(s): HTML
Link: Read online.

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