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Explore key learnings from Asana's journey in developing and implementing their first user-facing machine learning feature. This 34-minute conference talk delves into the process of building ML-powered features that run daily for millions of users in production. Gain valuable insights on modeling and embedding Asana Work Graph objects, monitoring model performance both offline and online, scaling batch and real-time ML platforms, and leveraging Databricks as a data and computation foundation. Learn how Asana overcame challenges in building ML capabilities, making this talk particularly beneficial for those aiming to enhance or establish ML initiatives within their organizations. Presented by Sarang Gupta, Data Scientist, and Zhan Shi, Data Infrastructure Engineer from Asana, this talk offers practical knowledge for data scientists and engineers looking to develop and deploy ML models effectively.
