4 recherche sur le mot-clé 'Neural networks'   

Hands-on generative adversarial networks with keras: your guide to implementing next-generation generative adversarial networks / Rafael Valle (2019)  

Public ISBD Titre : Hands-on generative adversarial networks with keras: your guide to implementing next-generation generative adversarial networks Type de document : livre Auteurs : Rafael Valle, Auteur Mention d'édition : 1st ed. Editeur : Birmingham, UK : Packt Publishing Année de publication : 2019 Importance : 259 p. ISBN/ISSN/EAN : 978-1-78953-820-5 Note générale : Code repository downloaded at GitHub : https://github.com/PacktPublishing/Hands-On-Generative-Adversarial-Networks-with-Keras Langues : Anglais (eng) Mots-clés : Machine learning  Neural networks  Python (Computer program language)  Computer programming  Imagery Résumé : Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. En ligne : https://www.packtpub.com/eu/big-data-and-business-intelligence/hands-generative- [...] Hands-on generative adversarial networks with keras: your guide to implementing next-generation generative adversarial networks [livre] / Rafael Valle, Auteur  . -  1st ed. . - Birmingham, UK : Packt Publishing, 2019 . - 259 p. ISBN : 978-1-78953-820-5 Code repository downloaded at GitHub : https://github.com/PacktPublishing/Hands-On-Generative-Adversarial-Networks-with-Keras Langues : Anglais (eng) Mots-clés : Machine learning  Neural networks  Python (Computer program language)  Computer programming  Imagery Résumé : Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. En ligne : https://www.packtpub.com/eu/big-data-and-business-intelligence/hands-generative- [...]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
69643	HAN_11_69643	Livre	Salle des ouvrages	11_Mathématiques	Sorti jusqu'au 22/10/2044

Models of the mind: how physics, engineering and mathematics have shaped our understanding of the brain / Grace Lindsay (2021)  

Public ISBD Titre : Models of the mind: how physics, engineering and mathematics have shaped our understanding of the brain Type de document : livre Auteurs : Grace Lindsay, Auteur Mention d'édition : 1st ed. Editeur : London : Bloomsbury Sigma Année de publication : 2021 Collection : Bloomsbury Sigma series Importance : 400 p. ISBN/ISSN/EAN : 978-1-4729-6642-1 Prix : 28.00 USD Langues : Anglais (eng) Mots-clés : Brain  Learning  Mental ability  Intelligence  Memory  Mathematics  Neural networks Résumé : Le site éditeur indique : The brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For over a century, a diverse array of researchers have been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when bringing the abstract world of mathematical modelling into contact with the messy details of biology. Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviors that brains command. Throughout Grace will look at the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics, and reveals in full the remarkable fruits of this endeavor. En ligne : https://www.bloomsbury.com/us/models-of-the-mind-9781472966421/ Models of the mind: how physics, engineering and mathematics have shaped our understanding of the brain [livre] / Grace Lindsay, Auteur  . -  1st ed. . - London : Bloomsbury Sigma, 2021 . - 400 p.. - (Bloomsbury Sigma series) . ISBN : 978-1-4729-6642-1 : 28.00 USD Langues : Anglais (eng) Mots-clés : Brain  Learning  Mental ability  Intelligence  Memory  Mathematics  Neural networks Résumé : Le site éditeur indique : The brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For over a century, a diverse array of researchers have been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when bringing the abstract world of mathematical modelling into contact with the messy details of biology. Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviors that brains command. Throughout Grace will look at the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics, and reveals in full the remarkable fruits of this endeavor. En ligne : https://www.bloomsbury.com/us/models-of-the-mind-9781472966421/

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
69737	LIN_11_69737	Livre	Salle des ouvrages	11_Mathématiques	Sorti jusqu'au 22/10/2044

Artificial intelligence: a guide for thinking humans / Melanie Mitchell (2020)  

Public ISBD Titre : Artificial intelligence: a guide for thinking humans Type de document : livre Auteurs : Melanie Mitchell, Auteur Mention d'édition : 1st pbk. ed. Editeur : New York : Picador Année de publication : 2020 Autre Editeur : New York : Farrar, Straus and Giroux Importance : 317 p. ISBN/ISSN/EAN : 978-1-250-75804-0 Prix : 18.00 USD Note générale : First Picador paperback edition; Langues : Anglais (eng) Mots-clés : Artificial intelligence  Machine learning  Neural networks  Social sciences Résumé : La 4ème de couv. indique : No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI's turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize-winning author of the modern classic Gödel, Escher, Bach, who explains why he is "terrified" about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell's humor and personal observations. This frank, lively book is an indispensable guide to understanding today's AI, its quest for "human-level" intelligence, and its impacts on the future for us all. Note de contenu : Voir aussi le site de l'auteur : https://melaniemitchell.me/aibook/ En ligne : https://us.macmillan.com/books/9781250758040 Artificial intelligence: a guide for thinking humans [livre] / Melanie Mitchell, Auteur  . -  1st pbk. ed. . - New York : Picador : New York : Farrar, Straus and Giroux, 2020 . - 317 p. ISBN : 978-1-250-75804-0 : 18.00 USD First Picador paperback edition; Langues : Anglais (eng) Mots-clés : Artificial intelligence  Machine learning  Neural networks  Social sciences Résumé : La 4ème de couv. indique : No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI's turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize-winning author of the modern classic Gödel, Escher, Bach, who explains why he is "terrified" about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell's humor and personal observations. This frank, lively book is an indispensable guide to understanding today's AI, its quest for "human-level" intelligence, and its impacts on the future for us all. Note de contenu : Voir aussi le site de l'auteur : https://melaniemitchell.me/aibook/ En ligne : https://us.macmillan.com/books/9781250758040

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
69738	MIT_11_69738	Livre	Salle des ouvrages	11_Mathématiques	Sorti jusqu'au 22/10/2044

Hands-on machine learning with Scikit-Learn, Keras and TensorFlow: concepts, tools, and techniques to build intelligent systems / Aurélien Géron (2019)  

Public ISBD Titre : Hands-on machine learning with Scikit-Learn, Keras and TensorFlow: concepts, tools, and techniques to build intelligent systems Type de document : livre Auteurs : Aurélien Géron, Auteur Mention d'édition : 2nd ed. Editeur : Sebastopol, California : O'Reilly Media Année de publication : 2019 Importance : 819 p. ISBN/ISSN/EAN : 978-1-4920-3264-9 Prix : 74.99 USD Note générale : All code is available on GitHub. Updated to TensorFlow 2 and the latest version of Scikit-Learn; List of errors and their corrections at : https://www.oreilly.com/catalog/errata.csp?isbn=9781492032649 Langues : Anglais (eng) Mots-clés : Machine learning  Artificial intelligence  Neural networks  Statistical methods  Python (Computer program language)  Computer programming En ligne : http://shop.oreilly.com/product/0636920142874.do Hands-on machine learning with Scikit-Learn, Keras and TensorFlow: concepts, tools, and techniques to build intelligent systems [livre] / Aurélien Géron, Auteur  . -  2nd ed. . - Sebastopol, California : O'Reilly Media, 2019 . - 819 p. ISBN : 978-1-4920-3264-9 : 74.99 USD All code is available on GitHub. Updated to TensorFlow 2 and the latest version of Scikit-Learn; List of errors and their corrections at : https://www.oreilly.com/catalog/errata.csp?isbn=9781492032649 Langues : Anglais (eng) Mots-clés : Machine learning  Artificial intelligence  Neural networks  Statistical methods  Python (Computer program language)  Computer programming En ligne : http://shop.oreilly.com/product/0636920142874.do

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
69644	GER_11_69644	Livre	Salle des ouvrages	11_Mathématiques	Sorti jusqu'au 22/10/2044