Amazon SageMaker

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost.

Case Studies

Showing 11 Amazon SageMaker Customer Success Stories

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Capillary Easily Expands to 30 Countries Using AWS

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Why Cerner Chose AWS to Power its Machine Learning and Artificial Intelligence, AWS San Francisco Summit 2018

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Condé Nast Goes All-In To The AWS Cloud

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Walter Scott Shares How DigitalGlobe Uses Amazon SageMaker

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Elevenia Instills a Data-Driven Culture with AWS Analytics Platform

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Gannett - Customer Case Study

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Mobiuspace - Customer Case Study

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John Nichols Describes PG&E’s Efforts to Use AWS to Innovate & Save Money

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Siemens Handles 60,000 Cyber Threats per Second Using AWS Machine Learning

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Mortgage Closings in 15 Minutes with Snapdocs on AWS

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Urbanbase launches services 20x faster with AWS

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