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Materials from my “Introduction to MLOps” workshop - a rapid, hands-on guide for senior engineers on moving from Jupyter notebooks to large-scale, automated ML on AWS. We cover data & model versioning with DVC, continuous training via GitHub Actions and SageMaker, containerised inference with ECR/ECS, and production monitoring through CloudWatch.
juice1000/Introduction-to-MLOps
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Materials from my “Introduction to MLOps” workshop - a rapid, hands-on guide for senior engineers on moving from Jupyter notebooks to large-scale, automated ML on AWS. We cover data & model versioning with DVC, continuous training via GitHub Actions and SageMaker, containerised inference with ECR/ECS, and production monitoring through CloudWatch.
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