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In the rapidly evolving field of IoT in manufacturing and transportation domains, machine learning features create significant value. By utilizing machine learning at the edge, manufacturers can gather insights faster, identify trends, identify patterns, and detect anomalies, all resulting in enhanced security and safety and cost savings.
Amazon SageMaker is a fully managed service that provides developers and data scientists with the ability to build, train, model, and deploy ML models for any use case with fully managed infrastructure, tools, and workflows quickly at scale. In this blog, written with our Premier AWS Partner, Ness Digital Engineering, we present the various options to compile, package, deploy, and run machine learning models across a fleet of devices at the edge.