IJMLAIDSE serves as a bridge between theory and practice, fostering collaboration among data scientists, AI researchers, machine learning engineers, and domain experts. The journal’s mission is to publish innovative research that accelerates progress in intelligent computing, automation, predictive analytics, and big data technologies. By promoting knowledge exchange across disciplines, IJMLAIDSE contributes to developing advanced computational models, ethical AI frameworks, and scalable data-driven solutions that support sustainable technological evolution.

IJMLAIDSE is published by Apex Academia Press, a reputed international publishing house committed to promoting open-access, peer-reviewed scholarly communication. Apex Academia Press upholds the highest standards of editorial quality, academic integrity, and ethical publishing practices across all its journals.

IJMLAIDSE welcomes a wide spectrum of scholarly submissions that reflect the dynamic growth of Artificial Intelligence, Machine Learning, and Data Science, including:

• Original Research Articles – Innovative studies presenting new algorithms, models, architectures, or empirical results that advance understanding and application in ML, AI, and data science.
• Review Articles – Comprehensive and critical analyses of current developments, trends, and challenges in subfields such as deep learning, natural language processing, computer vision, and big data analytics.
• Case Studies – Practical implementations of AI and ML systems demonstrating real-world applications in sectors like healthcare, finance, manufacturing, smart cities, and cybersecurity.
• Short Communications – Concise reports highlighting emerging techniques, recent experimental results, or conceptual breakthroughs that merit rapid dissemination.
• Editorials and Perspectives – Expert commentaries offering insights into ethical AI, evolving trends, and the societal impacts of intelligent technologies.