Building Real-Time ML Systems with Zipline + Chronon

Real-time ML use cases like personalization and risk decisioning come with a unique set of challenges: serving fresh feature values at low latency for inference, generating temporally consistent backfills for training, and building complex chains of on-demand, batch, and streaming transformations. In this roundtable, practitioners from Intuit, CreditKarma, Depop, and OpenAI will share how they use Zipline and the OSS Chronon project to solve these challenges and deploy real-time ML use cases in production.