Automated Machine Learning

Methods, Systems, Challenges

AvFrank Hutter,Lars Kotthoff

Inbunden, Engelska, 2019

Del i serien Springer Series on Challenges in Machine Learning

553 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2019-05-28
Mått:155 x 235 x 17 mm
Vikt:544 g
Format:Inbunden
Språk:Engelska
Serie:Springer Series on Challenges in Machine Learning
Antal sidor:219
Förlag:Springer Nature Switzerland AG
ISBN:9783030053178

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Recensioner i media

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

Innehållsförteckning

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.