Crear una plataforma de reparto basada en ML como DoorDash es una empresa compleja.
Tag Archives: ML
Uso de la distribución gamma para mejorar las predicciones de eventos de larga cola
Para DoorDash, poder predecir eventos de larga cola relacionados con los plazos de entrega es fundamental para garantizar que los pedidos de los consumidores lleguen cuando se espera.
Increasing Operational Efficiency with Scalable Forecasting
Forecasting is essential for planning and operations at any business — especially those where success is heavily indexed on operational efficiency.
Building a Gigascale ML Feature Store with Redis, Binary Serialization, String Hashing, and Compression
When a company with millions of consumers such as DoorDash builds machine learning (ML) models, the amount of feature data can grow to billions of records with millions actively retrieved during model inference under low latency constraints.
How Artificial Intelligence Powers Logistics at DoorDash
In May, DoorDash participated at the O’Reilly Artificial Intelligence Conference in New York where I presented on “How DoorDash leverages AI in its logistics engine.” In this post, I walk you through the core logistics problem at DoorDash and describe how we use Artificial Intelligence (AI) in our logistics engine.