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Machine Learning Engineering on AWS

<span xml:lang="en">Machine Learning Engineering on AWS: Build, scale, and secure machine learning systems and MLOps pipelines in production</span>

Lat, Joshua Arvin

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycleKey FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook DescriptionThere is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating...

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life...

Machine Learning Engineering on AWS: Build, scale, and...

Machine Learning Engineering on AWS: Build, scale, and secure machine learning systems and MLOps pipelines in production

Format

Machine Learning Engineering on AWS: Build, scale, and secure machine learning systems and MLOps pipelines in production

Joshua Arvin Lat

Joshua Arvin Lat

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