This project focuses on building a CI/CD pipeline that automates integration, testing, and deployment of AI/ML models into production environments efficiently and reliably.
Study ML model deployment lifecycle Design CI/CD pipeline for ML workflow Automate model packaging process Integrate automated model validation Configure testing using sample datasets Automate deployment to cloud environment Monitor model performance metrics Implement rollback for inaccurate predictions Track model version control Compare manual vs automated ML deployment Document system design and evaluation
