Data science and machine learning are at the heart of Faire’s industry-celebrated marketplace (a16z top-ranked marketplace) and drive powerful search, navigation, and risk functions which are powered by ML models that are trained on 3000+ features defined by our data scientists.
Previously, defining, backfilling and maintaining feature lifecycle was error-prone. Having a framework built on top of Airflow has empowered them to maintain and deploy their changes independently.
We will explore:
The talk will provide valuable insights into how Faire constructed a framework that builds datasets to train models. Plus, how empowering end-users with tools isn’t something to fear but frees up engineering teams to focus on strategic initiatives.