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“Efficient end-to-end ML workflows with integrated AWS tools”
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Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.
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Efficient end-to-end ML workflows with integrated AWS tools
SageMaker is a strong platform for building, training and deploying machine learning models at scale. The biggest advantages are its seamless integration with the AWS ecosystem, managed infrastructure and ability to handle end-to-end ML workflows efficiently. Features like SageMaker Studio, built-in algorithms, automated model training and scalable deployment endpoints have significantly reduced operational overhead for our team.



