This booklet introduces the most important basics of deep learning. It describes the very frequently used method of how a computer can learn using neural networks and training data and apply what it has learned to other questions similar to the training data. Two simple about 'one-pager' examples in Python show how training a neural network with forward and back propagation works and how the trained system can process simple forms of artificial thinking. The two short Python programs "Learning truth tables" and "Recognizing a questionnaire" are printed in full and are easy to follow.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This booklet introduces the most important basics of deep learning. It describes the very frequently used method of how a computer can learn using neural networks and training data and apply what it has learned to other questions similar to the training data. Two simple about 'one-pager' examples in Python show how training a neural network with forward and back propagation works and how the trained system can process simple forms of artificial thinking. The two short Python programs 'Learning truth tables' and 'Recognizing a questionnaire' are printed in full and are easy to follow. Artikel-Nr. 9783756832637
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Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This booklet introduces the most important basics of deep learning. It describes the very frequently used method of how a computer can learn using neural networks and training data and apply what it has learned to other questions similar to the training data. Two simple about 'one-pager' examples in Python show how training a neural network with forward and back propagation works and how the trained system can process simple forms of artificial thinking. The two short Python programs "Learning truth tables" and "Recognizing a questionnaire" are printed in full and are easy to follow. Artikel-Nr. 40477813/1
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