Automated Machine Learning by Frank Hutter

Automated Machine Learning by Frank Hutter

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

“This interesting collection should be useful for AutoML researchers seeking an overview and comprehensive bibliography” (Anoop Malaviya, Computing Reviews, June 14, 2021)

SKU	Non disponible
ISBN 13	9783030053178
ISBN 10	3030053172
Titre	Automated Machine Learning
Auteur	Frank Hutter
Série	The Springer Series On Challenges In Machine Learning
État	Non disponible
Type de reliure	Hardback
Éditeur	Springer Nature Switzerland AG
Année de publication	2019-05-28
Nombre de pages	219
Note de couverture	La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier.
Note	Non disponible