mlops

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Within machine learning, the hardest aspect often becomes deploying to production, until the time comes to address the issue. Applied at scale, this issue can hinder deployment, and at the worst, kill the project entirely. In this video, we will…

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In this session, learn more about Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that helps developers operate machine learning (ML) models on a fleet of edge devices and solve challenges with constraints and maintenance of ML models…

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AWS provides ML services for every use case so Startups of any size can launch immediately. AWS is among the top rated on Stanford’s 2020 deep learning benchmark, DAWNBench, for the fastest training time, lowest cost, lowest inference latency, and…

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Ever wonder how data scientists at digital freight marketplace Convoy are able to find the most cost-efficient trucking routes or how healthcare Startup SyntheticGestalt is taking the drug discovery process from 4 years down to 9 hours to accelerate scientific…

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AI and ML hold the promise of transforming industries, increasing efficiencies, and driving innovation. The key to machine learning success is scale. In this session, we cover how executives and managers who are looking to achieve success using ML at…

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AI and ML hold the promise of transforming industries, increasing efficiencies, and driving innovation. The key to machine learning success is scale. In this session, we cover how executives and managers who are looking to achieve success using ML at…

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Kubernetes and Kubeflow are becoming common tools for building ML Platforms, but require significant investment to configure the open source tools for reliability and scalability. SageMaker is a managed service and provides direct integrations with Kubernetes Operators and Kubeflow Pipeline…