StackAdapt on Efficient Analytics and Machine Learning for Trillions of Records Using AWS


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StackAdapt CTO Yang Han, Director of Engineering Afish Mahesaniya, and Manager, Data Science Ned Dimitrov present how StackAdapt auto-scaled over 500,000 requests per second, and handles analytics across trillions of event-based data using Redshift, Lambda, and Kinesis. They also showcase how they used EMR for machine learning across billions of historical records and 50,000 features.


Duration: 26:22
Publisher: Amazon Web Services
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