SageMaker Pipelines: CI/CD for ML with Terraform 🔁

1. 1Create a SageMaker Pipeline using Terraform to automate ML workflow
2. 2Configure pipeline stages for data preparation, model training, and deployment
3. 3Use Terraform to manage infrastructure and integrate with SageMaker
4. 4Test and validate pipeline execution to ensure reliable model retraining
5. 5Deploy and monitor SageMaker Pipeline using Terraform for CI/CD

Data scientists and engineers benefit from automated ML pipelines, ensuring reliable model retraining and deployment, while DevOps teams can leverage Terraform for infrastructure management

💡 SageMaker Pipelines automates the full ML lifecycle, reducing reliability risks and increasing efficiency

🚀 Automate ML lifecycle with SageMaker Pipelines & Terraform! 🔁