🚀 Led the implementation of inspection systems during my internship, utilizing YOLOv8 models for precise object detection and anomaly identification in product assemblies.🛠️ Employed tools such as OpenCV, TensorFlow, PyTorch, and Linux to optimize and deploy solutions, enhancing efficiency and accuracy in industrial inspection processes.📈 Successfully deployed these solutions on IoT devices, notably Raspberry Pi, resulting in significant quality improvements and a 50% reduction in processing time, demonstrating effective application of AI technology in real-world settings.

Developed a MERN Stack web portal with ReactJS and Clerk for secure user authentication, tailored for a dynamic Material Science forum. This platform supports collaboration among 200 students, enabling seamless sharing of new materials and detailed insights. 🌐💡Utilized Flask for the backend to deploy a variety of Machine Learning and NLP models customized for material science. These models are accessible via the web interface, enhancing usability and providing practical insights into material properties and applications. 🧪🚀Implemented containerization using Docker's multi-stage builds for both frontend and backend applications. Managed through Docker Compose, this setup ensures efficient communication and scalability across components. 🐳🔗Successfully hosted on AWS Cloud with a GoDaddy domain, leveraging Ubuntu EC2 for scalable computing, VPC/Subnet for robust network security, ACM for SSL/TLS encryption, ALB for load balancing, and Route53 for streamlined domain management. Implemented CI/CD pipelines via GitHub Actions for automated deployments post successful builds, ensuring reliability and timely updates. ☁️🚀

Build a movie recommendation engine using a hybrid recommendation technique based on collaborative filtering using cosine similarity. 🎥 Track user searches and store them in a database, utilizing a sorting algorithm to understand users' preferred movie types. Recommend movies based on this data using the recommendation system.Additionally, provide comprehensive movie descriptions along with character information using the IMDB API, implemented via Axios. 📜🎬Develop a user interactive website using HTML, JavaScript, and Tailwind CSS. Integrate the recommendation engine using Flask and deploy the website on Heroku. 🌐🚀

Develop a robust machine learning model using the XGBoost algorithm to predict the Air Quality Index (AQI) based on current weather conditions and pollutant levels in specific regions, achieving exceptional accuracy up to 98.25%. 🌤️Integrate LSTM time series forecasting to extend AQI predictions into the future, enabling proactive environmental planning and public health management. 📅Create a user-friendly web application that provides real-time AQI predictions tailored to users' locations, utilizing a REST API to fetch current weather and pollutant data. 🌍Deploy the application on Heroku using Docker containers for efficient scalability and reliability, ensuring seamless integration with CI/CD pipelines through GitHub Actions for automated builds and deployments. 🚀