Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition is a promotional item. To increase sales of the product. It can make you love it. Neural Networks for Pattern Recognition is a great product. Quality of work. Corresponds to a very And that it is affordable. I bought it from the Internet to use Neural Networks for Pattern Recognition . And it makes me very impressed. I introduced people I know. Its good to see. Effective The collar is the most in demand. Neural Networks for Pattern Recognition is important to the price. If you want to see detail of Neural Networks for Pattern Recognition . Please click on the Get Discount Price Here.
Neural Networks for Pattern Recognition Overview
This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layer perceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100 exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.
Neural Networks for Pattern Recognition Specifications
This book provides a solid statistical foundation for neural networks from a pattern recognition perspective. The focus is on the types of neural nets that are most widely used in practical applications, such as the multi-layer perceptron and radial basis function networks. Rather than trying to cover many different types of neural networks, Bishop thoroughly covers topics such as density estimation, error functions, parameter optimization algorithms, data pre-processing, and Bayesian methods. All topics are organized well and all mathematical foundations are explained before being applied to neural networks. The text is suitable for a graduate or advanced undergraduate level course on neural networks or for practitioners interested in applying neural networks to real-world problems. The reader is assumed to have the level of math knowledge necessary for an undergraduate science degree.
1. This page is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to amazon.com
2. Amazon, the Amazon logo, Endless, and the Endless logo are trademarks of Amazon.com, Inc. or its affiliates.
3. CERTAIN CONTENT THAT APPEARS ON THIS SITE COMES FROM AMAZON SERVICES LLC. THIS CONTENT IS PROVIDED AS IS AND IS SUBJECT TO CHANGE OR REMOVAL AT ANY TIME.
