Flyte is a workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others.
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To build a production-ready ML application and ensure its stability in the long run, we need to take care of a long checklist of requirements which include the ease with which the models could be iterated, reproducibility, infrastructure, automation,...
This article was originally published on the Lyft Engineering blog on March 25th, 2022. Introduction In a data-driven company like Lyft, data is the core backbone for many application components. Data analytics gives us the incentives for improving e...
2021 was a fantastic year for Flyte — 100+ features and 20+ integrations were added, 1000+ community members joined us, production deployments across the globe grew ten-fold, integrations paved the way for greater adoption, and the number of use case...
With no more low-level cloud configurations
This blog is with reference to a talk titled “Efficient Data Parallel Distributed Training with Flyte, Spark & Horovod”, presented by Katrina Rogan and Ketan Umare at OSPOCon 2021, Seattle. To get the ball rolling, let’s understand what the title imp...
An End-to-end Online Machine Learning Application
