Projects
Vehicle Insurance Prediction
This project implements a complete MLOps pipeline for vehicle insurance prediction, following a fully modular coding structure. It covers key stages such as data ingestion, preprocessing, model training, evaluation, and deployment, with Docker integration for containerization. Tools like GitHub Actions can be easily incorporated for CI/CD workflows, enhancing automation and production-readiness.
Diamond Price Prediction
Designed and implemented a Diamond Price Prediction system with a strong focus on MLOps and DevOps practices. Built a modular ML pipeline using Python and Scikit-Learn, automated version control with Git, GitHub, and DVC, and streamlined CI/CD workflows using Jenkins and Docker. Deployed an interactive prediction app with Streamlit, emphasizing automation, scalability, and production-readiness.
Movie Recommender System
A personalized recommendation system using collaborative filtering to suggest movies based on user preferences. Built with Python,Scikit-learn, and optimized with TF-IDF vectorization for enhanced performance. The project features an interactive Streamlit web app, deployed on Heroku.
