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.

Vol. 2024 (2024)

Published: 2024-01-03

Green Building Techniques: Under The Umbrella of the Climate Framework Agreement

Ali Saleh, Noah Saleh, Obed Ali, Raed Hasan, Omar Ahmed , Azil Alias, Khalil Yassin



A Short Review on Supervised Machine Learning and Deep Learning Techniques in Computer Vision

Ahmed Adil Nafea, Saeed Amer Alameri , Russel R Majeed, Meaad Ali Khalaf , Mohammed M AL-Ani


View All Issues