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MLOps Engineering at Scale: Deploying Pytorch Models on Aws

Posted By: hill0
MLOps Engineering at Scale: Deploying Pytorch Models on Aws

MLOps Engineering at Scale: Deploying Pytorch Models on Aws
English | 2022 | ISBN: 1617297763 | 250 Pages | EPUB | 5 MB

Deploying a machine learning model into a fully realized production system usually requires painstaking work by an operations team creating and managing custom servers. Cloud Native Machine Learning helps you bridge that gap by using the pre-built services provided by cloud platforms like Azure and AWS to assemble your ML system’s infrastructure. Following a real-world use case for calculating taxi fares, you’ll learn how to get a serverless ML pipeline up and running using AWS services. Clear and detailed tutorials show you how to develop reliable, flexible, and scalable machine learning systems without time-consuming management tasks or the costly overheads of physical hardware.

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