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Automated Machine Learning Overview

Author

Listed:
  • Budjač Roman
  • Nikmon Marcel
  • Schreiber Peter
  • Zahradníková Barbora

    (Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu Č. 25, 917 24 Trnava, Slovak Republic)

  • Janáčová Dagmar

    (Tomas Bata University of Zlin, Faculty of Applied Informatics, Department of Automation and Control Engineering, Nad Stráněmi 4511, 760 05 Zlín, Czech Republic)

Abstract

This paper aims at deeper exploration of the new field named auto-machine learning, as it shows promising results in specific machine learning tasks e.g. image classification. The following article is about to summarize the most successful approaches now available in the A.I. community. The automated machine learning method is very briefly described here, but the concept of automated task solving seems to be very promising, since it can significantly reduce expertise level of a person developing the machine learning model. We used Auto-Keras to find the best architecture on several datasets, and demonstrated several automated machine learning features, as well as discussed the issue deeper.

Suggested Citation

  • Budjač Roman & Nikmon Marcel & Schreiber Peter & Zahradníková Barbora & Janáčová Dagmar, 2019. "Automated Machine Learning Overview," Research Papers Faculty of Materials Science and Technology Slovak University of Technology, Sciendo, vol. 27(45), pages 107-112, September.
    • Handle: RePEc:vrs:repfms:v:27:y:2019:i:45:p:107-112:n:15
    DOI: 10.2478/rput-2019-0033
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