Aim
The Shodh Sagar Journal of Artificial Intelligence and Machine Learning (SSJAIML) aims to serve as a premier international platform for academics, researchers, professionals, and students from around the globe to share and disseminate both theoretical and practical knowledge in the fields of Artificial Intelligence (AI) and Machine Learning (ML). By fostering a multidisciplinary discourse, SSJAIML seeks to contribute to the ongoing advancements in these fields, pushing the boundaries of what is possible in technology and its applications in society.

Scope
SSJAIML welcomes submissions that address innovative and impactful research in the areas of AI and ML, including but not limited to:
• Foundational Theory and Algorithms in AI and ML, including deep learning, reinforcement learning, neural networks, evolutionary algorithms, and theoretical underpinnings of these domains.
• AI Systems and Architectures, covering the design, implementation, and evaluation of systems that exhibit intelligent behavior in complex environments.
• Machine Learning Applications, such as natural language processing, computer vision, robotics, and predictive analytics, with a focus on novel applications and use cases.
• Ethical, Societal, and Policy Implications of AI and ML, exploring the ethical considerations, societal impacts, regulatory issues, and the future of work in the age of automation.
• Human-AI Interaction, including studies on human-centered AI, explainable AI, and user experience design for AI systems.
• Data Science and Big Data Analytics, focusing on the intersection of ML and big data, including data mining, pattern recognition, and data-driven decision-making.
• Emerging Technologies and Trends in AI and ML, such as quantum computing's impact on AI, neurotechnological advancements, and AI in healthcare and environmental sciences.

SSJAIML is committed to a rigorous peer-review process to ensure the publication of high-quality research. The journal encourages submissions of original research articles, review articles, case studies, and technical reports that push forward the field of AI and ML.