Actively building projects in ML, AI, and predictive analytics — from healthcare classification to demand forecasting. Expanding into quantitative finance.
End-to-end ML pipelines: from raw data to evaluated models.
End-to-end ML web app predicting salary ranges from job features. Built with scikit-learn and deployed on Render — fully live and usable. Covers feature engineering, model training, and a FastAPI + vanilla JS interface for real-time predictions.
Time-series forecasting for NYC taxi trips — enabling smarter fleet allocation and route optimization across boroughs. Deployed live on Streamlit.
Personalized suggestions via collaborative filtering based on user behavior patterns and item similarity metrics.
ML-based early detection for CKD using Random Forest on clinical tabular data. Key predictors: serum creatinine, hemoglobin, BP, and albumin. Full EDA and cross-validation pipeline.
Full pipeline: exploration, preprocessing, modeling, and visualization.
Open to collaborations, internships, and opportunities in DS, ML, and FinTech. Always happy to talk data or AI × finance.