THURSDAY: A Web Platform to Support AutoML
Authors: 
Chase Carthen, Christopher Lewis, Vinh Le, Alireza Tavakkoli, Frederick Harris, Sergiu DascaluAuthors Info & Claims
Pages 41 - 46
Abstract
THURSDAY is a web platform that aids users in building machine learning models by providing easily accessible tools to either create models manually, or through the use of automated machine learning (AutoML) libraries like AutoKeras. As part of THURSDAY’s key innovations, users are given the opportunity to configure and run multiple machine learning models. The results of these model executions can then be compared with built-in performance metrics. Finally, THURSDAY allows users to analyze hyperparameter changes, as well as the changes created by AutoML libraries, in order to provide a vital tool that aids in the revision of existing models. To meet the high volume demands of machine learning, THURDAY adopted a microservice-based design pattern that supports containerization, orchestration, and scalabability. In this paper, the design, implementation, and impact of the THURSDAY system is explored in detail. In order to evaluate the capability of THURSDAY, its core functionality is compared against similar platforms that provide machine learning support.
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May 2022
81 pages
ISBN:9781450397605
DOI:10.1145/3543895
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Published: 26 January 2023
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ACIT 2022: The 9th International Conference on Applied Computing & Information Technology
May 25 - 26, 2022
Virtual Event, USA
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