Automated machine learning methods (16 résultats)

Etat : New.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,400grams, ISBN:9781608459698.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,400grams, ISBN:9781608459698. …

Paperback. Etat : New. 1. The item is brand new, never used or read. It's in perfect condition and may include supplements and/or access codes or come shrink-wrapped.

Etat : New.

Etat : New. In English.

Hardback. Etat : Good. 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.

Hardback. Etat : Good. 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.

Etat : New. 1st edition NO-PA16APR2015-KAP.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Hardcover. Etat : Brand New. 219 pages. 9.75x6.50x0.75 inches. In Stock.

Etat : New. Print on Demand.

Hardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Etat : New. PRINT ON DEMAND.

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.