#295: Creating a DevOps Workflow for Machine Learning Mod...

What this episode covers

Training your ML model is just one part of the puzzle; retaining it and deploying into production on a regular basis is key for great business outcomes. Simon speaks with John Calhoun (Machine Learning Specialist, AWS) about how to implement this in your business using the open source AWS Sagemaker Build CloudFormation. Shownotes: Source Code: https://github.com/aws-samples/aws-sagemaker-build Blog Post: https://aws.amazon.com/blogs/machine-learning/automated-and-continuous-deployment-of-amazon-sagemaker-models-with-aws-step-functions/

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How long is this episode of AWS Podcast?

This episode is 18 minutes long.

When was this AWS Podcast episode published?

This episode was published on February 2, 2019.

What is this episode about?

Training your ML model is just one part of the puzzle; retaining it and deploying into production on a regular basis is key for great business outcomes. Simon speaks with John Calhoun (Machine Learning Specialist, AWS) about how to implement this in...

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