KEENsight: Cloud Based Collaborative Environment for Streamlining Machine Learning Development
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Machine learning has transitioned from an individualistic approach to a collaborative one, enabling the collective effort to address increasingly complex challenges as they arise. One challenge that emerges is the management of a collaborative development process in machine learning projects. This paper outlines a collaborative environment KEENsight that leverages the benefits of a collaborative approach by orchestrating various open source tools. It establishes an optimal setting for code collaboration, model generation, data sharing, and the utilization of computational resources not limited to a single location. Through the integrating of these tools, KEENsight aims to streamline the development process and enhance productivity in machine learning.
Details
Originalsprache | Englisch |
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Titel | 15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024 |
Herausgeber (Verlag) | IEEE |
Seiten | 1-8 |
Seitenumfang | 8 |
ISBN (elektronisch) | 9798350368833 |
ISBN (Print) | 979-8-3503-6884-0 |
Publikationsstatus | Veröffentlicht - 19 Juli 2024 |
Peer-Review-Status | Ja |
Konferenz
Titel | 15th International Conference on Information, Intelligence, Systems & Applications |
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Kurztitel | IISA 2024 |
Veranstaltungsnummer | 15 |
Dauer | 17 - 19 Juli 2024 |
Webseite | |
Ort | Grand Arsenali |
Stadt | Chania, Crete |
Land | Griechenland |
Externe IDs
ORCID | /0000-0001-8719-5741/work/175219892 |
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ORCID | /0000-0002-7396-1983/work/175220788 |
Scopus | 85215819568 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Codes, Collaboration, Computational modeling, Data models, Machine learning, Productivity, Data Management, Machine Learning Operations, Machine Learning