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are state-of-the-art, trainable algorithms that emulate certain major aspects in the functioning of the human brain. This gives them a unique, self-training ability, the ability to formalize unclassified information and, most importantly, the ability to make forecasts based on the historical information they have at their disposal.This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. It describes the use of neural networks in machine learning: deep learning, recurrent networks, and other supervised and unsupervised machine-learning algorithms.
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