The Babylonian Journal of Machine Learning (BJML) (EISSN: 3006-5429) is a specialized publication dedicated to the exploration and integration of modern machine learning methodologies. As a platform for researchers and scholars, the journal focuses on the intersection of cutting-edge advancements in machine learning. Through high-quality articles, it fosters interdisciplinary discussions aimed at propelling forward the field of machine learning research.

Current Issue

Vol. 2025 (2025)

In Progress

Published: 2025-01-10

Articles

Analysis of the performance of algorithms (K-Means, Farthest First, Hierarchical) Using the data analysis and modeling tool Weka

Mohammed Basil Abdulkareem

13-26

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DOI: https://doi.org/10.58496/BJML/2025/002

Integrating Machine Learning and Genetic Algorithms to Enhance Gene-Disease Classification: An XBNet-Based Framework

Rana Khalid Hamad

1-12

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DOI: https://doi.org/10.58496/BJML/2025/001
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