AWS Public Sector Blog

Tag: machine learning on AWS

Amazon SageMaker Studio Lab helps educators focus on teaching rather than technology

The browser-based computational notebook tool, Jupyter, provides students and educators with an interactive learning environment to accelerate programming learning. But setting up collaborative Jupyter notebooks at the classroom and institutional level can be time-consuming and costly. Amazon SageMaker Studio Lab is a no-cost service built on Jupyter notebooks that takes care of the configuration and security of setting up multi-user Jupyter notebook environments – so educators can focus on teaching and learners can accelerate their journey in ML.

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What we learned at Amazon re:MARS 2022 for the public sector

The Amazon re:MARS 2022 conference brought together thought leaders, technical experts, and groundbreaking companies and organizations that are transforming what’s possible in machine learning (ML), automation, robotics, and space. Advancements in these fields are the engines that will drive innovation for the next 100 years. Read on to learn about announcements from re:MARS related to the public sector, plus some of the innovative organizations and companies that were onsite to inspire guests with breakthrough technologies and ideas.

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How public sector agencies can identify improper payments with machine learning

To mitigate synthetic fraud, government agencies should consider complementing their rules-based improper payment detection systems with machine learning (ML) techniques. By using ML on a large number of disparate but related data sources, including social media, agencies can formulate a more comprehensive risk score for each individual or transaction to help investigators identify improper payments efficiently. In this blog post, we provide a foundational reference architecture for an ML-powered improper payment detection solution using AWS ML services.

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Using AWS to help students find an affordable college

Moneythink is an education technology nonprofit providing big solutions to help with college affordability, accessibility, and student loan debt. We built DecidED, a web app that runs on AWS and provides students across the country with guidance and support to understand financial aid options and budgeting for college costs. Our work gives students the cost transparency necessary to make clear decisions about their futures, and is especially beneficial for historically marginalized students, as they often lack resources due to institutionally imposed barriers.

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How Skillshare increased their click-through rate by 63% with Amazon Personalize

Skillshare is the largest global online learning community for creativity. They offer thousands of inspiring classes for creative and curious people on topics including illustration, design, photography, video, freelancing, and more. Skillshare wanted their members to easily discover relevant content with a seamless discovery process of personalized recommendations. Skillshare decided to test Amazon Personalize from AWS to make these data-fueled recommendations for members with machine learning. This blog post describes their Amazon Personalize solution architecture, their AWS Step Functions process, and the results of their experiment.

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Personalizing studying with machine learning: Course Hero’s approach

Different students learn in different ways. While many traditional classrooms continue to rely on a one-size-fits-all approach, Course Hero delivers personalized learning to every student through its innovative, machine learning (ML)-powered online platform. Operating under the slogan “Master your Classes,” Course Hero was founded with the vision of a world where every student graduates confident and prepared. The platform provides students access to study materials, including study guides, class notes, and practice problems. The service also includes on-demand access to subject matter expert tutors, available to help students 24/7.

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