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Neural Networks for Pattern Recognition


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Rather than try to cover different types of neural networks, Bishop thoroughly covers topics such as density estimation, error functions, parameter optimization algorithms, data pre-processing, and Bayesian methods. Suitable text for graduate or advanced undergraduate level course on neural networks or for practitioners interested in applying neural networks to real-world problems.

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