Title
Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback)),New
Delivery time: 8-12 business days (International)
This is the first comprehensive treatment of feedforward 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 multilayer 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 uptodate work will benefit anyone involved in the fields of neural computation and pattern recognition.
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Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main focus of 'Neural Networks for Pattern Recognition' by Christopher M. Bishop? A: The book provides a comprehensive treatment of feed-forward neural networks specifically from the perspective of statistical pattern recognition.
- Q: How many pages does the book contain? A: The book contains a total of 504 pages.
- Q: What are the key topics covered in this book? A: Key topics include modeling probability density functions, multi-layer perceptron models, radial basis function networks, error functions, learning and generalization in neural networks, and Bayesian techniques.
- Q: Is this book suitable for beginners in neural networks? A: While the book introduces basic concepts, it is designed as a text with over 100 exercises, making it suitable for readers with some prior knowledge in the field.
- Q: What is the publication date of this book? A: The book was published on January 18, 1996.
- Q: What edition of the book is available? A: This is the first edition of 'Neural Networks for Pattern Recognition'.
- Q: What is the condition of the book being sold? A: The book is listed as being in 'Good' condition.
- Q: What type of binding does this book have? A: The book is available in paperback binding.
- Q: Who is the author of 'Neural Networks for Pattern Recognition'? A: The author of the book is Christopher M. Bishop.
- Q: What type of exercises are included in the book? A: The book includes over 100 exercises designed to help readers understand and apply the concepts presented.