AWS re:Invent 2021 - Implementing MLOps practices with Amazon SageMaker, featuring Vanguard

Implementing MLOps practices helps data scientists and operations engineers collaborate to prepare, build, train, deploy, and manage models at scale. During this session, explore the breadth of MLOps features in Amazon SageMaker that help you provision consistent model development environments, automate ML workflows, implement CI/CD pipelines for ML, monitor models in production, and standardize model governance capabilities. Then, hear from Vanguard as they share their journey enabling MLOps to achieve ML at scale for their polyglot model development platforms using Amazon SageMaker features, including SageMaker projects, SageMaker Pipelines, SageMaker Model Registry, and SageMaker Model Monitor.
Learn more about re:Invent 2021 at bit.ly/3IvOLtK
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[@BasselHaidar]

Fantastic session showcasing SageMaker's MLOps capabilities. Two thumbs way up Shelbee!

[@alzeNL]

Shelbee is excellent because I found her engaging to listen to, the examples given practical and useful. More Shelbee please. The Vanguard section I drifted off very quickly, I tried coming back to it but it just wasnt as engaging. Id suggest watching upto the 31 minute mark to get the most out of this video.

[@aritrachaudhury7738]

Thank you for this enriching session. It gives out a good overview of AWS Sagemaker UI and MLOPS native capabilities.

[@puresoul9537]

I like your way of teaching❤

[@ArunKumar-bp5lo]

if i want to make a personal pipelines and project it will be a paid service ?? can't i get for free as it's not commercial purpose

[@awssupport]

Hi Arun. 🙂 You may find this document helpful: go.aws/free-tier-overview. It's an overview of AWS Free Tier. If you'd like, you can use this to review available options by searching for your preferred product in the "Explore Top Product Categories" section. ^SA