Automated machine learning : methods, systems, challenges / Frank Hutter, Lars Kotthoff, Joaquin Vanschoren, editors.
Hutter, Frank, editor.; Kotthoff, Lars, editor.; Vanschoren, Joaquin, editor.
2019
Q325.5
Available Online

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Title Automated machine learning : methods, systems, challenges / Frank Hutter, Lars Kotthoff, Joaquin Vanschoren, editors.
ISBN 9783030053185 (electronic book)
3030053180 (electronic book)
9783030053178
DOI https://doi.org/10.1007/978-3-030-05318-5
https://doi.org/10.1007/978-3-030-05
Published Cham, Switzerland : Springer, 2019.
Language English
Description 1 online resource (xiv, 219 pages) : illustrations.
Other Standard Identifiers 10.1007/978-3-030-05318-5 doi
10.1007/978-3-030-05
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary 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.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed June 19, 2019).
Added Author Hutter, Frank, editor.
Kotthoff, Lars, editor.
Vanschoren, Joaquin, editor.
Series Springer series on challenges in machine learning.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1 Hyperparameter Optimization
2 Meta-Learning
3 Neural Architecture Search
4 Auto-WEKA
5 Hyperopt-Sklearn
6 Auto-sklearn
7 Towards Automatically-Tuned Deep Neural Networks
8 TPOT
9 The Automatic Statistician
10 AutoML Challenges.

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