Détail de l'auteur
Auteur Shigeyuki TAKANO |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche
Thinking Machines : Machine Learning and Its Hardware Implementation / Shigeyuki TAKANO / ELSEVIER SCIENCE (2021)
Titre : Thinking Machines : Machine Learning and Its Hardware Implementation Type de document : e-book Auteurs : Shigeyuki TAKANO Editeur : ELSEVIER SCIENCE Année de publication : 2021 ISBN/ISSN/EAN : 9780128182796 Note générale : copyrighted Langues : Anglais (eng) Résumé : Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks.This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning. Presents a clear understanding of various available machine learning hardware accelerator solutions that can be applied to selected machine learning algorithms Offers key insights into the development of hardware, from algorithms, software, logic circuits, to hardware accelerators Introduces the baseline characteristics of deep neural network models that should be treated by hardware as well Presents readers with a thorough review of past research and products, explaining how to design through ASIC and FPGA approaches for target machine learning models Surveys current trends and models in neuromorphic computing and neural network hardware architectures Outlines the strategy for advanced hardware development through the example of deep learning accelerators Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88930550 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=550487
LIBRARY - Campus Rouen
NEOMA Business School
pmb
-
59 Rue Taittinger, 51100 Reims
-
00 33 (0)3 26 77 46 15
Library Campus Reims
-
1 Rue du Maréchal Juin, BP 215
76825 Mont Saint Aignan cedex -
00 33 (0)2 32 82 58 26