A Lifecycle-Oriented Taxonomy of Open-Source Tools for Machine Learning

Abstract: Machine learning (ML) offers various tools, frame-works and platforms for resolving complex problems in compu-tational science and engineering. Machine learning frameworks have emerged as the cornerstone of modern research and in-novation. It redefines how knowledge is produced, validated, and disseminated. Open-source machine learning frameworks are emerging as a promising way to solve the challenges of large datasets, real-time constraints and heterogeneous system components. This study provides an extensive overview of open source tools based on the ML lifecycle. These tools are evaluated based on their purpose and key features for each stage of lifecycle, assisting researchers and practitioners in making informed decisions according to their requirements. The key challenges are identified and future research directions are also outlined.

Hamza Mallam Musa Mohammad, Isa Hussain Adam Mohammed, Abdullah Bajaber, Syed Abdur Rahman, Anas Sani and Atif Naseer. “A Lifecycle-Oriented Taxonomy of Open-Source Tools for Machine Learning”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.5 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170501

@article{Mohammad2026,
title = {A Lifecycle-Oriented Taxonomy of Open-Source Tools for Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170501},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170501},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {5},
author = {Hamza Mallam Musa Mohammad and Isa Hussain Adam Mohammed and Abdullah Bajaber and Syed Abdur Rahman and Anas Sani and Atif Naseer}
}