Isbn: 9780956372819 - artificial intelligence engines: a tutorial introduction to the mathematics of deep learning (27 risultati)

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Paperback. Condizione: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Paperback. Condizione: Good. The brain has always had a fundamental advantage over conventional computers: it can learn. However, a new generation of artificial intelligence algorithms, in the form of deep neural networks, is rapidly eliminating that advantage. Deep neural networks rely on adaptive algorithms to master a wide variety of tasks, including cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, backgammon and Go, at super-human levels of performance. In this richly illustrated book, key neural network learning algorithms are explained informally first, followed by detailed mathematical analyses. Topics include both historically important neural networks (e.g. perceptrons), and modern deep neural networks (e.g. generative adversarial networks). Online computer programs, collated from open source repositories, give hands-on experience of neural networks, and PowerPoint slides provide support for teaching. Written in an informal style, with a comprehensive glossary, tutorial appendices (e.g. Bayes' theorem), and a list of further readings, this is an ideal introduction to the algorithmic engines of modern artificial intelligence.…

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Paperback or Softback. Condizione: New. Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning. Book.

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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The brain has always had a fundamental advantage over conventional computers: it can learn. However, a new generation of artificial intelligence algorithms, in the form of deep neural networks, is rapidly eliminating that advantage. Deep neural networks rely on adaptive algorithms to master a wide variety of tasks, including cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, backgammon and Go, at super-human levels of performance. In this richly illustrated book, key neural network learning algorithms are explained informally first, followed by detailed mathematical analyses. Topics include both historically important neural networks (e.g. perceptrons), and modern deep neural networks (e.g. generative adversarial networks). Online computer programs, collated from open source repositories, give hands-on experience of neural networks, and PowerPoint slides provide support for teaching. Written in an informal style, with a comprehensive glossary, tutorial appendices (e.g. Bayes' theorem), and a list of further readings, this is an ideal introduction to the algorithmic engines of modern artificial intelligence.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &Uumlber den AutorJames V Stone is an Honorary Associated Professor at the University of Sheffield, UK.KlappentextrnrnThe brain has always had a fundamental advantage over conventional computers: it can learn. Howeve.…

Taschenbuch. Condizione: Neu. Artificial Intelligence Engines | A Tutorial Introduction to the Mathematics of Deep Learning | James V Stone | Taschenbuch | Kartoniert / Broschiert | Englisch | 2019 | Sebtel Press | EAN 9780956372819 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …