This project involved developing a comprehensive text summarization system with a focus on the full MLOps lifecycle, from CI/CD integration to cloud deployment. Key Accomplishments: -CI/CD Pipeline: Automated deployment with GitHub Actions for efficient and error-free builds. -Dockerized App: Ensured consistent environment replication and deployment using Docker. -AWS Deployment: --EC2: Hosted the application on scalable and secure virtual machines. --ECR: Stored Docker images for easy access and deployment. -Model Evaluation: Assessed summarization quality using ROUGE and SacreBLEU metrics. -Technologies Used: --NLP Libraries: Transformers, NLTK --Tools: FastAPI, Docker, GitHub Actions, AWS EC2/ECR --Focus of the Project: The main goal was to develop a production-ready pipeline with a seamless development, testing, and deployment process, rather than focusing solely on the model. -GitHub Repository: https://github.com/Divyansh0108/E2E-text-summarization The project highlights expertise in full MLOps life cycle, including CI/CD, containerization, and cloud deployment, demonstrating the ability to manage and deploy robust applications.