Tag: Machine Learning

Through the AWS Open Data Sponsorship Program, customers are making over 300 PB of high-value, cloud-optimized data available for public use. All publicly available datasets can be found in the Registry of Open Data on AWS and are now also discoverable on Exchange. This quarter, AWS released 66 new or updated datasets. Read this post to learn more.

In this post, we walk through creating a Retrieval Augmented Generation (RAG)–powered chat assistant using Amazon SageMaker AI and Amazon Kendra to query donor data on AWS.

Healthcare systems around the world are facing unprecedented challenges, from addressing chronic conditions to supporting aging populations and addressing emerging health threats, and it has become unmistakably clear that technology is no longer just a support function—it’s a force-multiplier that can transform health outcomes. At AWS, we’ve witnessed a remarkable shift as health agencies worldwide increasingly choose cloud computing to drive innovation, enhance research capabilities, and ultimately, improve patient outcomes.

We’re excited to announce the expansion of AWS HealthLake to the EU (Dublin) Region, marking a significant milestone in our commitment to supporting healthcare organizations across the European Union (EU). Read this post to learn more.

Technical Safety BC (TSBC) regulates the safe installation and operation of technical systems (electrical, gas, boiler, elevator, etc.) in British Columbia. This post showcases how the TSBC built a machine learning operations (MLOps) solution using AWS to streamline production model training and management to process public safety inquiries more efficiently.

Read this post to learn how Change.org built a next-generation recommender on AWS that turned more awareness into action—boosting petition signatures by 30 percent.

Mid-Hudson Valley Federal Credit Union (MHVFCU) needed to automate their tools and develop advanced forecasting capabilities to make informed decisions for deposit management and growth to maximize benefit for their members. For this purpose, MHVFCU leadership sought a solution that would not only save time in data preparation and analysis but also provide accurate forecasts for balances across four key deposit products: savings, checking, certificate deposits (CDs), and money market. Read this post to learn about the solution they built with AWS.

In this post, we explore how Amazon SageMaker Canvas can make machine learning accessible and actionable for nonprofit organizations. We highlight key features that allow your nonprofit to harness the power of machine learning without data science expertise or dedicated engineering teams.

The Greenwood Genetic Center (GGC) is a nonprofit institute organized to provide clinical genetic services, diagnostic laboratory testing, educational programs and resources, and research in the field of medical genetics. To make its medical records accessible to providers, the GGC created a data warehouse to serve as a single repository for its data, where clinicians have access to an all-encompassing view of patients’ records. Read this post to learn more.

Many government agencies, like the National Oceanic and Atmospheric Administration (NOAA), participate in the AWS Open Data Sponsorship Program. In this post, we discuss how to use NOAA datasets in the Registry of Open Data on AWS using Amazon Bedrock Knowledge Bases.