Tag: datasets

Immigration, Refugees, and Citizenship Canada (IRCC) faced a significant challenge: the need to perform complex fuzzy string matching across two different datasets. IRCC embarked on a transformative project that redefined its data processing capabilities and showcased the power of cloud computing in overcoming substantial data challenges. Instead of dealing with months of undifferentiated heavy lifting activities, IRCC successfully used Amazon Elastic Compute Cloud (Amazon EC2) instances to complete the work in a only few days. Read this post to learn more.

The Amazon Web Services (AWS) Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. Through this program, customers are making more than 100 petabytes (PB) of high-value, cloud-optimized data available for public use. This past quarter, AWS released 21 new or updated datasets. What will you build with these datasets?

About 4.5 million electroencephalogram (EEG) tests are performed in the US each year. That’s more than if every person in Oregon, Connecticut, or Iowa got an EEG. Because they provide insights into brain activity and not just structure, EEGs are one of the most common tests ordered by doctors to help make a diagnosis for people with brain problems. The Brain Data Science Platform (BDSP), hosted on Amazon Web Services (AWS), is increasing EEG accessibility through cooperative data sharing and research enabled by the cloud. Read this post to learn more.

The Amazon Web Services (AWS) Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. Through this program, customers are making more than 100 petabytes (PB) of high-value, cloud-optimized data available for public use. Read this blog post to learn about the 34 new or updated datasets that were released in the first quarter.

Generative artificial intelligence (AI) allows anyone to leverage machine learning (ML) capabilities using natural language, and it is extremely intuitive to use. When users are able to search, analyze, and draw conclusions in seconds—from extensive information that exists across their organization or the internet—they can make more informed decisions at speed. This blog post takes a quick look at some of the generative AI considerations public sector organizations need to take.

Amazon Rekognition, a code-free automated machine learning (AutoML) service from Amazon Web Services (AWS), showed impeccable diagnostic performance in categorizing various retinal diseases using optical coherence tomography (OCT) scans. This blog post details the steps to use Amazon Rekognition Custom Labels to train a model that categorizes retinal diseases and the process of training and fine-tuning convolutional neural networks (CNNs), the standard deep learning methodology.

At the end of 2022, Northwestern University’s Kellogg School of Management had a decision to make. The on-premises SQL server used by faculty and students had reached the end of its life, and the school needed to identify a cost-effective way forward while ensuring that the datasets would remain highly available for researchers to use on demand. After weighing various options, Kellogg worked with Amazon Web Services (AWS) to create a data lake that fit its unique needs.

To improve safety and convenience, transportation agencies amass a substantial volume of data. However, these organizations encounter challenges in data accuracy validation due to issues related to data quality and occasional missing information. With the incorporation of new artificial intelligence and machine learning capabilities from Amazon Web Services (AWS), they can take advantage of no-code solutions to identify and address data gaps.

This quarter, AWS released 34 new or updated datasets on the Register of Open Data. What will you build with these datasets? Read through this blog post for inspiration.

This quarter, AWS released 36 new or updated datasets. As July 16 is Artificial Intelligence (AI) Appreciation Day, the AWS Open Data team is highlighting three unique datasets that are analysis-ready for AI. What will you build with these datasets?