Tech Talks: Building Competing Models Using Apache Spark DataFrames from Credit Karma on Vimeo. In this video, Abdulla Al-Qawasmeh, Engineering Manager, talks about the important role model calibration plays in the performance of Credit Karma’s recommendation system, and how to build predictive recommendation models using Apache Spark DataFrames.
Some time ago, we held a coding event to show proof of concept for Prophecy, our new general prediction platform. Our legacy platform was outdated, running a minimum viable product that we endlessly hacked to scale. We knew machine learning could help our users get more tailored offers, recommendations to help them build their credit, […]
Originally posted in Scott Livingston’s blog At Credit Karma, my team maintains a service powered by a multi node Akka cluster. Akka is a framework for building distributed, concurrent, and message-driven systems in Scala. It helps us easily scale our service, and gives us some resilience when problems inevitably happen in production. In this post, I’ll cover two […]