aws-samples/mlops-e2e
MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
This project helps MLOps engineers set up a robust, automated pipeline for machine learning models. It takes your raw data and ML code, and automatically trains, tests, and deploys a production-ready model endpoint. Data scientists and ML engineers who need to frequently update and deploy models without manual intervention would use this.
158 stars.
Use this if you need a fully automated, end-to-end CI/CD system to manage the lifecycle of your machine learning models on AWS.
Not ideal if you are looking for a simple, one-off model deployment or do not require an automated MLOps pipeline.
Stars
158
Forks
106
Language
TypeScript
License
MIT-0
Category
Last pushed
Mar 26, 2026
Commits (30d)
0
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