How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

This is a guest post co-written with Fred Wu from Sportradar.

Sportradar is the world’s leading sports technology company, at the intersection between sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across …

How the UNDP Independent Evaluation Office is using AWS AI/ML services to enhance the use of evaluation to support progress toward the Sustainable Development Goals

The United Nations (UN) was founded in 1945 by 51 original Member States committed to maintaining international peace and security, developing friendly relations among nations, and promoting social progress, better living standards, and human rights. The UN is currently made …

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

This is joint post co-written by Leidos and AWS. Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets.

Leidos has …

How VMware built an MLOps pipeline from scratch using GitLab, Amazon MWAA, and Amazon SageMaker

This post is co-written with Mahima Agarwal, Machine Learning Engineer, and Deepak Mettem, Senior Engineering Manager, at VMware Carbon Black

VMware Carbon Black is a renowned security solution offering protection against the full spectrum of modern cyberattacks. With terabytes of …

How Marubeni is optimizing market decisions using AWS machine learning and analytics

This post is co-authored with Hernan Figueroa, Sr. Manager Data Science at Marubeni Power International.

Marubeni Power International Inc (MPII) owns and invests in power business platforms in the Americas. An important vertical for MPII is asset management for renewable …

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