Deploy an end-to-end machine learning application using CI/CD pipelines and GitHub Actions on AWS cloud infrastructure. Learn how to set up Docker workflows, configure IAM users, create ECR repositories, launch EC2 instances, and implement app runners. Follow along with step-by-step instructions covering prerequisites, Docker setup, AWS configurations, and running the complete workflow. Gain practical experience in deploying production-ready ML projects using cloud services and automation tools.
How to Deploy End to End ML Projects in Production AWS Cloud Using CI CD Pipeline