LyftLearn is Lyft’s ML Platform. It is a machine learning infrastructure built on top of Kubernetes that powers diverse applications such as dispatch, pricing, ETAs, fraud detection, and support. In a previous blog post, we explored the architecture and challenges of the platform.
In this post, we will focus on how we utilize the compute layer of LyftLearn to profile model features and predictions and perform anomaly detection at scale.
In this post, we will focus on how we utilize the compute layer of LyftLearn to profile model features and predictions and perform anomaly detection at scale.