Built a machine learning model to classify potato diseases using leaf images, enabling early detection and improved crop management.

Built a machine learning model to predict house prices based on various features, enabling accurate real estate valuations and informed decision-making. This project demonstrates end-to-end MLOps fundamentals: moving a machine learning model from a Jupyter notebook into a deployable, scalable, production-grade REST API.

Developed a web app that predicts diseases based on user-input symptoms using machine learning algorithms for early diagnosis support.

Implemented an emotion detection system using OpenCV for real-time face detection and a Convolutional Neural Network (CNN) to classify emotions from facial expressions.