AWS Machine Learning Blog
Category: Case Study
How NSF’s iHARP researchers are enabling active learning for polar ice analysis using Amazon SageMaker and Amazon A2I
The University of Maryland, Baltimore County’s Bina lab is a multidisciplinary research lab for employing advanced computer vision, machine learning (ML), and remote sensing techniques to discover new knowledge of our environment, especially in the Arctic and Antarctic regions. The lab’s work is supported by NSF BIGDATA awards (IIS-1947584, IIS-1838230), the NSF HDR Institute award […]
How Imperva expedites ML development and collaboration via Amazon SageMaker notebooks
This is a guest post by Imperva, a solutions provider for cybersecurity. Imperva is a cybersecurity leader, headquartered in California, USA, whose mission is to protect data and all paths to it. In the last few years, we’ve been working on integrating machine learning (ML) into our products. This includes detecting malicious activities in databases, […]
Virtu Financial enables its customers to apply advanced analytics and machine learning on trade and market data by provisioning Amazon SageMaker
This is a guest post by Erin Stanton, who currently runs the Global Client Support organization for Virtu Analytics. Virtu Financial is a leading provider of financial services and products that uses cutting-edge technology to deliver liquidity to the global markets and innovative, transparent trading solutions to its clients. Virtu uses its global market-making expertise […]
Ounass increases its revenue using Amazon SageMaker with a Word2vec based recommender system
Based in Dubai, Ounass is the Middle East’s leading ecommerce platform for luxury goods. Scouring the globe for leading trends, Ounass’s expert team reports on the latest fashion updates, coveted insider information, and exclusive interviews for customers to read and shop. With more than 230,000 unique catalog items spanning multiple brands and several product classes—including […]
Personalizing wellness recommendations at Calm with Amazon Personalize
This is a guest post by Shae Selix (Staff Data Scientist at Calm) and Luis Lopez Soria (Sr. AI/ML Specialist SA at AWS). Today, content is proliferating. It’s being produced in many different forms by a host of content providers, both large and small. Whether it’s on-demand video, music, podcasts, or other forms of rich […]
Arçelik hosts global AWS DeepRacer League using new LIVE feature to educate over 200 employees on machine learning
This is a guest post by Pınar Köse Kulacz, Innovation Director at Arçelik. Arçelik, the leading global manufacturer of household appliances, has collaborated with AWS since 2019 to increase efficiency and innovate on new services. Here at Arçelik, we believe that data and artificial intelligence provide a critical advantage over competitors in the global consumer […]
Kinect Energy uses Amazon SageMaker to Forecast energy prices with Machine Learning
The Amazon ML Solutions Lab worked with Kinect Energy recently to build a pipeline to predict future energy prices based on machine learning (ML). We created an automated data ingestion and inference pipeline using Amazon SageMaker and AWS Step Functions to automate and schedule energy price prediction. The process makes special use of the Amazon […]