Dekorationsartikel gehören nicht zum Leistungsumfang.
Artificial Intelligence Engines
A Tutorial Introduction to the Mathematics of Deep Learning
Taschenbuch von James V Stone
Sprache: Englisch

39,10 €*

inkl. MwSt.

Versandkostenfrei per Post / DHL

Lieferzeit 4-7 Werktage

Kategorien:
Beschreibung
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.
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.
Über den Autor
James V Stone is an Honorary Associated Professor at the University of Sheffield, UK.
Details
Erscheinungsjahr: 2019
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 218
ISBN-13: 9780956372819
ISBN-10: 0956372813
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Stone, James V
Hersteller: Sebtel Press
Maße: 229 x 152 x 13 mm
Von/Mit: James V Stone
Erscheinungsdatum: 01.04.2019
Gewicht: 0,323 kg
preigu-id: 116083837
Über den Autor
James V Stone is an Honorary Associated Professor at the University of Sheffield, UK.
Details
Erscheinungsjahr: 2019
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 218
ISBN-13: 9780956372819
ISBN-10: 0956372813
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Stone, James V
Hersteller: Sebtel Press
Maße: 229 x 152 x 13 mm
Von/Mit: James V Stone
Erscheinungsdatum: 01.04.2019
Gewicht: 0,323 kg
preigu-id: 116083837
Warnhinweis

Ähnliche Produkte

Ähnliche Produkte