Tag: Machine Learning

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.

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.