Git workflow for active learning - a development methodology proposal for data-centric AI projects

  • As soon as Artificial Intelligence (AI) projects grow from small feasibility studies to mature projects, developers and data scientists face new challenges, such as collaboration with other developers, versioning data, or traceability of model metrics and other resulting artifacts. This paper suggests a data-centric AI project with an Active Learning (AL) loop from a developer perspective and presents ”Git Workflow for AL”: A methodology proposal to guide teams on how to structure a project and solve implementation challenges. We introduce principles for data, code, as well as automation, and present a new branching workflow. The evaluation shows that the proposed method is an enabler for fulfilling established best practices.

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Metadaten
Author:Fabian StielerORCiDGND, Bernhard BauerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1040539
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/104053
ISBN:978-989-758-647-7OPAC
ISSN:2184-4895OPAC
Parent Title (English):Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2023), April 24-25, 2023, in Prague, Czech Republic
Publisher:SciTePress
Place of publication:Setúbal
Editor:Hermann Kaindl, Mike Mannion, Leszek Maciaszek
Type:Conference Proceeding
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/04/27
Tag:Active Learning; Software Engineering; Machine Learning; Machine Learning Operations
GND-Keyword:Machine Learning; Software Engineering
First Page:202
Last Page:213
DOI:https://doi.org/10.5220/0011988400003464
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Software & Systems Engineering
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik / Professur Softwaremethodik für verteilte Systeme
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)

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