AWS Machine Learning Blog

Category: Case Study

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 […]

Read More

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 […]

Read More

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 […]

Read More

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 […]

Read More

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 […]

Read More