Machine Learning is Going Real-Time
This talk covers different levels of real-time machine learning, their use cases, challenges, and adoption.
Scaling Online ML Predictions to Meet DoorDash Logistics Engine and Marketplace Growth
As DoorDash business grows, the online ML prediction volume grows exponentially to support the various Machine Learning use cases, such as the ETA predictions, the Dasher assignments, the personalized restaurants and menu items recommendations, and …
Rethinking Feature Stores with Feast and Tecton
Feature stores have emerged as a pivotal component in the modern machine learning stack. They solve some of the toughest challenges in data for machine learning, namely feature management, storage, validation, serving, and reuse. However, many …