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An automated-ML library that automates model training completely using simple APIs. Moreover, it provides curated data analysis modules for preprocessing, anomaly/outlier removal, sanity check(bias-variance tradeoffs), data splitter and explainability of model predictions with visualizations.
Autonomous multi-agent Data Science pipeline — upload a CSV, get a trained model, EDA charts, and an executive report. Zero manual intervention. Built with CrewAI · FastAPI · React · XGBoost · WebSockets.
Automated end-to-end MLOps pipeline for predicting customer purchase likelihood of a wellness tourism package, enabling data-driven marketing through CI/CD-enabled model training and deployment.
An algorithmic bias audit and fairness evaluation of an emergency department clinical triage model using Azure Machine Learning and macro-balanced mitigation strategies.