In recent years, machine learning (ML) has proven useful in helping organizations increase efficiency and foster innovation. As ML matures, the focus naturally shifts from experiment to production. ML processes need to be streamlined, standardized, and automated to build, train, deploy, and manage models in a consistent and reliable manner. Multi-year IT issues such as security, high availability, scalability, control and automation are also critical. Large ML models will not be of much use if they are unable to provide fast and accurate forecasts for enterprise applications 24/7 and on any scale.

We started in November 2017 Amazon SageMaker helps ML engineers and data scientists not only build the best models, but also use them effectively. We have since stepped up our efforts to provide our customers with the most comprehensive service hundreds of features covering all stages of the ML lifecycle, such as data tagging, data preparation, feature design, prejudice detection, AutoML, training, tuning, hosting, explanability, tracking, and automation. We have also integrated these features into a web-based development environment, Amazon SageMaker Studio.

Thanks to the commendable ML features SageMakerTens of thousands of AWS customers in all industries have deployed ML to accelerate business processes, create innovative User Experiences, improve revenue and reduce costs. Examples are Engie (energy), Deliveroo (food delivery), SNCF (railway) Nerdwallet (financial services), Autodesk (computer aided design), Formula 1 (car racing), as well as your own Amazon filling technologies and Amazon robot.

Today, we are pleased to announce that in his latest Enterprise MLOps Platforms report Bradley Shimmin, Chief Analyst, Omdiapaid SageMaker the following treatment: “AWS is a direct leader in Omdia’s comparative review of enterprise MLOps platforms. At almost every scale, the company significantly outperformed its competitors, producing a steady value throughout the ML lifecycle. AWS provides well-differentiated functionality that addresses the very impressive concerns of the company’s AI practitioners, who seek not only to operate but also to expand AI throughout the business.


You can download complete report to learn more.

To get started
Curious Amazon SageMaker? developer’s guide shows you how to set it up and start using your laptops in minutes.

As always, we look forward to your feedback. You can send it through regular AWS support contacts or send it AWS forum for Amazon SageMaker.

– Julien


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