xboost

AI-Powered Quick Commerce Delivery Intelligence System — End-to-end analytics & ML prediction dashboard for Blinkit, Zepto, Swiggy Instamart | 9.4L orders | Random Forest R²=0.9658 | Streamlit + Plotly + XGBoost | Live Deployed

Complete ML pipeline for Titanic survival prediction using Logistic Regression, Random Forest, XGBoost, and SVM includes EDA, preprocessing, tuning, and feature importance.

AI-powered project management assistant using ML to predict task delays, classify project risk, and optimize resource allocation. Features an NLP query interface, automated reporting, and a Streamlit dashboard. Built with FastAPI, scikit-learn, and XGBoost — runs locally, no cloud dependency required.

An end-to-end Machine Learning project focused on analyzing historical sales data to forecast future inventory demand. By predicting exact sales trends, this system minimizes inventory holding costs and prevents stockout situations, optimizing the overall supply chain.