Tag: Machine Learning

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.

To support education leaders on their AI journey, we’ve developed a practical guide that maps real-world challenges to proven AI use cases. While not exhaustive, these examples serve as inspiration—highlighting what others have achieved and helping you explore how AI can address your institution’s priorities

Cloud computing, automation, and AI are driving a new wave of modernization in public services. They’re helping to make them more accessible, responsive, and cost-effective. The Kingdom of Bahrain shows how this can be done. In this blog, we explore how, through a cloud-first strategy, the country has modernized its public services, boosted economic growth, and developed a culture of innovation.

Today, Amazon Web Services (AWS) launched the 2025 AWS Imagine Grant cycle in six countries. The AWS Imagine Grant is a public grant opportunity open to registered nonprofit organizations who are using cloud technology to accelerate their missions. Now in its eighth year, the AWS Imagine Grant is expanding to nonprofits beyond the US, UK, and Ireland, adding Canada, Australia, and New Zealand.

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.

Academic research IT departments around the world face the same challenge: how to balance their existing on-premises infrastructure with the opportunities of cloud computing. At the Supercomputing 2024 (SC24) conference, Amazon Web Services hosted a panel featuring two research IT leaders: Circe Tsui, associate director of solutions architecture at Emory University in the Office of Information Technology, and Dr. Robert Shen, director of the RMIT AWS Supercomputing Hub (RACE) at the Royal Melbourne Institute of Technology (RMIT). During the panel, Tsui and Shen shared how their institutions use AWS to augment and enhance their research operations with more scalability, security, and collaboration alongside their on-premises infrastructure. Read this post to learn more.

Higher education institutions are under increasing pressure to demonstrate the effectiveness of their programs and provide students with a clear path to degree completion. Data analytics can help these institutions proactively identify and support at-risk students, allowing them to develop personalized intervention strategies to improve student retention and graduation rates. In this post, we’ll explore how Amazon Redshift ML, a powerful machine learning (ML) capability within the Amazon Redshift data warehouse, can enable higher education leaders to quickly predict student outcomes and communicate insights to key stakeholders.

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on Amazon Web Services (AWS). AWS works with data providers to democratize access to data by making it available to the public for analysis on AWS; develop new cloud-based techniques, formats, and tools that lower the cost of working with data; and encourage the development of communities that benefit from access to shared datasets. The full list of publicly available datasets are on the Registry of Open Data on AWS and are now also discoverable on AWS Data Exchange. This quarter, AWS released 53 new or updated datasets and you can learn more about them in this post.