AWS Machine Learning Blog

Category: Case Study

Optimize F1 aerodynamic geometries via Design of Experiments and machine learning

FORMULA 1 (F1) cars are the fastest regulated road-course racing vehicles in the world. Although these open-wheel automobiles are only 20–30 kilometers (or 12–18 miles) per-hour faster than top-of-the-line sports cars, they can speed around corners up to five times as fast due to the powerful aerodynamic downforce they create. Downforce is the vertical force […]

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The Intel®3D Athlete Tracking (3DAT) scalable architecture deploys pose estimation models using Amazon Kinesis Data Streams and Amazon EKS

This blog post is co-written by Jonathan Lee, Nelson Leung, Paul Min, and Troy Squillaci from Intel.  In Part 1 of this post, we discussed how Intel®3DAT collaborated with AWS Machine Learning Professional Services (MLPS) to build a scalable AI SaaS application. 3DAT uses computer vision and AI to recognize, track, and analyze over 1,000 […]

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3xLOGIC uses Amazon Rekognition Streaming Video Events to provide intelligent video analytics on live video streams to monitoring agents

3xLOGIC is a leader in commercial electronic security systems. They provide commercial security systems and managed video monitoring for businesses, hospitals, schools, and government agencies. Managed video monitoring is a critical component of a comprehensive security strategy for 3xLOGIC’s customers. With more than 50,000 active cameras in the field, video monitoring teams face a daily […]

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How Searchmetrics uses Amazon SageMaker to automatically find relevant keywords and make their human analysts 20% faster

Searchmetrics is a global provider of search data, software, and consulting solutions, helping customers turn search data into unique business insights. To date, Searchmetrics has helped more than 1,000 companies such as McKinsey & Company, Lowe’s, and AXA find an advantage in the hyper-competitive search landscape. In 2021, Searchmetrics turned to AWS to help with […]

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How Moovit turns data into insights to help passengers avoid delays using Apache Airflow and Amazon SageMaker

This is a guest post by Moovit’s Software and Cloud Architect, Sharon Dahan. Moovit, an Intel company, is a leading Mobility as a Service (MaaS) solutions provider and creator of the top urban mobility app. Moovit serves over 1.3 billion riders in 3,500 cities around the world. We help people everywhere get to their destination […]

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Part 4: How NatWest Group migrated ML models to Amazon SageMaker architectures

The adoption of AWS cloud technology at NatWest Group means moving our machine learning (ML) workloads to a more robust and scalable solution, while reducing our time-to-live to deliver the best products and services for our customers. In this cloud adoption journey, we selected the Customer Lifetime Value (CLV) model to migrate to AWS. The […]

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Part 3: How NatWest Group built auditable, reproducible, and explainable ML models with Amazon SageMaker

This is the third post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS Professional Services to build a new machine learning operations (MLOps) platform. This post is intended for data scientists, MLOps engineers, and data engineers who are interested in building ML pipeline templates with Amazon SageMaker. […]

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Part 2: How NatWest Group built a secure, compliant, self-service MLOps platform using AWS Service Catalog and Amazon SageMaker

This is the second post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS Professional Services to build a new machine learning operations (MLOps) platform. In this post, we share how the NatWest Group utilized AWS to enable the self-service deployment of their standardized, secure, and compliant MLOps […]

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Part 1: How NatWest Group built a scalable, secure, and sustainable MLOps platform

This is the first post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS to build a scalable, secure, and sustainable machine learning operations (MLOps) platform. This initial post provides an overview of the AWS and NatWest Group joint team implemented Amazon SageMaker Studio as the standard for […]

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Predict residential real estate prices at ImmoScout24 with Amazon SageMaker

This is a guest post by Oliver Frost, data scientist at ImmoScout24, in partnership with Lukas Müller, AWS Solutions Architect. In 2010, ImmoScout24 released a price index for residential real estate in Germany: the IMX. It was based on ImmoScout24 listings. Besides the price, listings typically contain a lot of specific information such as the […]

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