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Today we’re joined by Gary Ren, a machine learning engineer for the logistics team at DoorDash.
In our conversation, we explore how machine learning powers the entire logistics ecosystem. We discuss the stages of their “marketplace,” and how using ML for optimized route planning and matching affects consumers, dashers, and merchants. We also talk through how they use traditional mathematics, classical machine learning, potential use cases for reinforcement learning frameworks, and challenges to implementing these explorations.
The complete show notes for this episode can be found at twimlai.com/go/405!
Check out our upcoming event at twimlai.com/twimlfest
By Sam Charrington4.7
422422 ratings
Today we’re joined by Gary Ren, a machine learning engineer for the logistics team at DoorDash.
In our conversation, we explore how machine learning powers the entire logistics ecosystem. We discuss the stages of their “marketplace,” and how using ML for optimized route planning and matching affects consumers, dashers, and merchants. We also talk through how they use traditional mathematics, classical machine learning, potential use cases for reinforcement learning frameworks, and challenges to implementing these explorations.
The complete show notes for this episode can be found at twimlai.com/go/405!
Check out our upcoming event at twimlai.com/twimlfest

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