This post is co-written by Hesham Fahim from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses...

Today, companies are establishing feature stores to provide a central repository to scale ML development across business units and data science teams. As feature...

This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office...

Deploying high-quality, trained machine learning (ML) models to perform either batch or real-time inference is a critical piece of bringing value to customers. However,...

Foundation models are large deep learning models trained on a vast quantity of data at scale. They can be further fine-tuned to perform a...

Today, we’re happy to announce updates to our Amazon SageMaker Experiments capability of Amazon SageMaker that lets you organize, track, compare and evaluate machine learning...

Amazon SageMaker Training Managed Warm Pools gives you the flexibility to opt in to reuse and hold on to the underlying infrastructure for a...

In an increasingly data-centric world, enterprises must focus on gathering both valuable physical information and generating the information that they need but can’t easily...

Organizations of all sizes are striving to grow their business, improve efficiency, and serve their customers better than ever before. Even though the future...

Amazon Lookout for Vision provides a machine learning (ML)-based anomaly detection service to identify normal images (i.e., images of objects without defects) vs anomalous...

Across all industries, machine learning (ML) models are getting deeper, workflows are getting more complex, and workloads are operating at larger scales. Significant effort...

Posted by Krishna Giri Narra, Software Engineer, Google, and Chiyuan Zhang, Research Scientist, Google Research Ad technology providers widely use machine learning (ML) models to...