The International Journal of AI, Machine Learning & Data Science (IJAIMLDS) publishes high-quality, peer-reviewed research that advances both the theory and practical applications of artificial intelligence, machine learning, and data science.

The journal provides an international platform for researchers and practitioners to share innovative ideas, novel methodologies, and impactful discoveries that contribute to the rapidly evolving AI landscape.

Scope of the Journal

The journal welcomes original contributions in, but not limited to, the following areas:

• Deep learning architectures and algorithms
• Machine learning theory and applications
• Big data analytics and data mining
• Natural language processing (NLP)
• Computer vision and pattern recognition
• Explainable AI, fairness, accountability, and ethics in AI
• Reinforcement learning and autonomous systems
• Data science methodologies and reproducible research
• AI applications in healthcare, finance, education, and industry

Types of Contributions

• Original research articles
• Review and survey papers
• Technical notes and short communications
• Application-focused studies with real-world impact