Projects

Machine learning model to predict customer churn using ensemble methods with 94% accuracy. This project helps businesses identify customers at risk of leaving and take proactive retention measures.

Interactive dashboard for sales forecasting using time series analysis and Streamlit. The dashboard allows business users to visualize historical sales data and generate forecasts with adjustable parameters.

NLP tool that analyzes customer reviews and social media posts to determine sentiment. Built with transformers and deployed as a web app for real-time analysis.

Deep learning model using LSTM networks to predict stock prices. Features technical indicators, multiple timeframes, and risk assessment metrics for informed trading decisions.