OptimaPrime : From Data to Decisions, Autonomously. Researchers and data practitioners spend significant time switching between tools for data analysis, model development, hyperparameter tuning, and result interpretation. This fragmented workflow slows experimentation and requires substantial expertise in machine learning. We propose an "Agentic AI Research Assistant" that autonomously understands user goals, analyzes uploaded datasets, performs exploratory data analysis, selects suitable machine learning models, and optimizes them using automated hyperparameter tuning frameworks such as "Optuna". The agent can generate executable code, train models, evaluate performance, explain results, and recommend improvements through a conversational interface. By combining "Agentic AI", automated ML workflows, and intelligent decision-making, the system reduces the time required for experimentation while enabling researchers and students to focus on insights rather than implementation details. The solution delivers faster, more accurate, and interpretable predictive analysis with minimal human intervention.
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