Machine learning has transitioned from an individ-
ualistic 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.
%0 Conference Paper
%1 sherpa2024keensight
%A Sherpa, Lincoln
%A Attar Khorasani, Sima
%A Sankar, Rajasekar
%A Müller-Pfefferkorn, Ralph
%A Ghiasvand, Siavash
%B The Fifteenth International Conference on Information, Intelligence, Systems and Applications
%C Crete, Greece
%D 2024
%K yaff
%T KEENsight: Cloud based Collaborative Environment for Streamlining Machine Learning Development
%X Machine learning has transitioned from an individ-
ualistic 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.
@inproceedings{sherpa2024keensight,
abstract = {Machine learning has transitioned from an individ-
ualistic 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.},
added-at = {2025-02-24T08:15:09.000+0100},
address = {Crete, Greece},
author = {Sherpa, Lincoln and Attar Khorasani, Sima and Sankar, Rajasekar and Müller-Pfefferkorn, Ralph and Ghiasvand, Siavash},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/27f67833c1f0bbbe8824ecda602fd5b2a/scadsfct},
booktitle = {The Fifteenth International Conference on Information, Intelligence, Systems and Applications},
copyright = {All rights reserved},
interhash = {2117a90a85c6857d4f6370e884060efe},
intrahash = {7f67833c1f0bbbe8824ecda602fd5b2a},
keywords = {yaff},
month = jun,
shorttitle = {{KEENsight}},
timestamp = {2025-08-24T00:51:26.000+0200},
title = {KEENsight: Cloud based Collaborative Environment for Streamlining Machine Learning Development},
year = 2024
}