In an AWS Machine Learning workflow, you want to set up a continuous integration and delivery (CI/CD) pipeline using AWS CodePipeline that includes stages for data validation, model training, automated testing, and production deployment. What is the most effective sequence of these stages to ensure a streamlined, automatic transition from development to production?