AWS re:Invent 2020: How to create fully automated ML workflows with Amazon SageMaker Pipelines
Machine learning (ML) workflows are hard to build because you need to create hundreds of code packages for data preparation, model training, and model deployment and stitch them together so they run as a sequence of steps. In this session, learn about Amazon SageMaker Pipelines, the world’s first ML CI/CD service designed to be accessible for every developer and data scientist. SageMaker Pipelines brings CI/CD pipelines to ML, reducing the months of coding previously required to just a few hours. See a demonstration of how you can create an automated ML workflow with just a few clicks and learn how SageMaker Pipelines manages dependencies and orchestrates the workflow. Learn more about re:Invent 2020 at http://bit.ly/3c4NSdY Subscribe: More AWS videos http://bit.ly/2O3zS75 More AWS events videos http://bit.ly/316g9t4 #AWS #AWSEvents
AWS re:Invent 2020: Amazon SageMaker Feature Store: Store, discover, & share features for ML apps
AWS re:Invent 2020: Implementing MLOps practices with Amazon SageMaker
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Organize, Track, and Evaluate ML Training Runs With Amazon SageMaker Experiments
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Inside Anthropic, the $965 Billion AI Juggernaut | The Circuit
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AWS Summit ANZ 2022 - End-to-end MLOps for architects (ARCH3)
CI/CD Explained: The DevOps Skill That Makes You 10x More Valuable
Building, training and deploying machine learning models with Amazon SageMaker (July 2020)
