AWS Government, Education, & Nonprofits Blog

Tag: Machine Learning

Using Data in Education: Four Steps to Success

Educators are increasingly adopting data analytics to understand and address gaps in education. This includes educators in higher education seeking to personalize student-learning experiences and improve learning outcomes, as well as policymakers looking to understand and scale effective teaching methods, increase efficiency and teaching capacity, among other concerns. AWS’s “Four Steps to Success” offers a high-level guide for leaders seeking to adopt new tools to make better use of the data they are collecting.

Read More

Helping to End Future Famines with Machine Learning

The United Nations, World Bank, and International Committee of the Red Cross (ICRC) with support from Amazon Web Services and other technology companies, recently launched the Famine Action Mechanism (FAM). The FAM is the first global mechanism dedicated to preventing future famines. In the past, responses to these devastating events have often come too late, once many lives have already been lost.

Read More

Estimating Hurricane Wind Speeds with Machine Learning

Better estimates of hurricane wind speeds can lead to better decisions around evacuations and general hurricane response planning, saving both lives and property. Hurricane windspeed estimates are currently made using the manual Dvorak technique. The National Hurricane Center releases them every three to six hours. Artificial intelligence (AI) experts with the IMPACT team at NASA’s Marshall Space Flight Center and Development Seed created the Deep Learning-Based Hurricane Intensity Estimator to automate this process.

Read More

Highlights from the 2018 IMAGINE: A Better World, A Global Education Conference

Timed with the 2018 back-to-school season, nearly 600 students, educators, university presidents, college administrators, superintendents, and business leaders from 14 different countries met in Seattle, Washington, to discuss how the cloud can address challenges and opportunities facing education. The conference revolved around three core themes: innovation and transformation, the role of machine learning in education, and building the workforce of tomorrow.

Read More

Fishackathon: Supporting the Sustainability of our Oceans and Fisheries

According to the World Wildlife Fund, approximately three billion people in the world rely on both wild-caught and farmed seafood as their primary source of protein; yet the United Nations Food and Agricultural Organization estimates that eighty-five percent of marine fish stocks are either fully exploited or overfished. To combat this, the annual Fishackathon, first organized by the U.S. Secretary of State’s Office of Global Partnerships in 2014 and organized this year in partnership with HackerNest, took place in over 40 cities around the globe.

Read More

AWS Educate Members Now Receive Exclusive Access to Content on Udacity’s Nanodegree Program on Machine Learning

AWS Educate is committed to providing students and educators with resources needed to accelerate cloud learning, which is why we have collaborated with Udacity – an online education provider for lifelong learners – to bring our members access to skills, knowledge, and practice for today’s machine learning technology. Beginning on May 18th, AWS Educate members will receive an exclusive benefit of $200 worth of free content on their Machine Learning Engineer Nanodegree Program. With Udacity, AWS Educate members can master valuable machine learning skills and use their AWS Promotional Credits to gain hands-on experience with cutting-edge AWS Machine Learning technologies like Amazon SageMaker.

Read More

How DigitalGlobe Uses Amazon SageMaker to Manage Machine Learning at Scale

If you have ever searched for directions, called an Uber, or looked up a trailhead, you have used DigitalGlobe’s imagery or information derived from it. DigitalGlobe went all-in on AWS to meet the growing demand for commercial geo-intelligence, migrating its entire 18-year imagery archive to the cloud. The company used AWS Snowmobile to move 100 petabytes of data to the cloud, allowing it to move away from large file-transfer protocols and delivery workflows.

Read More