Скачать или смотреть 🔁 Automate Your ML Workflow using AWS Step Functions | MLOps with SageMaker & CI/CD Pipelines

Discover how to automate end-to-end Machine Learning workflows using AWS Step Functions in this comprehensive tutorial. Learn how ML practitioners and development teams can collaborate effectively while maintaining clear ownership boundaries using CI/CD pipelines and AWS services like SageMaker, Cloud9, CodeCommit, and CodePipeline.

🧠 What You’ll Learn:

Real-world ML process automation using Step Functions

Introduction to State Machines in ML pipelines

Empowering ML engineers with Step Functions Data Science SDK

Hands-on guide to YAML/JSON-based workflow orchestration

Full CI/CD pipeline with Cloud9, CDK, CodeCommit, and SageMaker

Building deployable artifacts and managing IAM roles for ML automation

Using Workflow Studio for low-code ML orchestration

🚀 Whether you’re a Machine Learning engineer, Data Scientist, or DevOps specialist, this video will help you scale and streamline ML model development and deployment with AWS-native tools.

Github: https://github.com/creative-h

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