Automatic machine learning: methods, systems, challenges

Frank Hutter, Lars Kotthoff, J. Vanschoren

Research output: Book/ReportBook editingAcademicpeer-review

Abstract

This open access book presents the first comprehensive overview of general methods in Automatic Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first international challenge of AutoML systems. The 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. 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. Many of the recent machine learning successes crucially rely on human experts, who select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters; however the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself.
LanguageEnglish
Place of PublicationNew York
PublisherSpringer
Number of pages242
ISBN (Electronic)978-3-030-05318-5
ISBN (Print)978-3-030-05317-8
DOIs
StatePublished - 2019

Publication series

NameChallenges in Machine Learning
PublisherSpringer
ISSN (Print)2520-131X

Fingerprint

Learning systems
Automation
Students

Keywords

  • Automatic Machine Learning

Cite this

Hutter, F., Kotthoff, L., & Vanschoren, J. (2019). Automatic machine learning: methods, systems, challenges. (Challenges in Machine Learning). New York: Springer. DOI: 10.1007/978-3-030-05318-5
Hutter, Frank ; Kotthoff, Lars ; Vanschoren, J./ Automatic machine learning : methods, systems, challenges. New York : Springer, 2019. 242 p. (Challenges in Machine Learning).
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Hutter, F, Kotthoff, L & Vanschoren, J 2019, Automatic machine learning: methods, systems, challenges. Challenges in Machine Learning, Springer, New York. DOI: 10.1007/978-3-030-05318-5

Automatic machine learning : methods, systems, challenges. / Hutter, Frank; Kotthoff, Lars; Vanschoren, J.

New York : Springer, 2019. 242 p. (Challenges in Machine Learning).

Research output: Book/ReportBook editingAcademicpeer-review

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Hutter F, Kotthoff L, Vanschoren J. Automatic machine learning: methods, systems, challenges. New York: Springer, 2019. 242 p. (Challenges in Machine Learning). Available from, DOI: 10.1007/978-3-030-05318-5