“We run a Databricks on S-III, but we pull data into Databricks from Snowflake, so we have a connection between the two.”
quote is from the automated transcript, cleaned for reading:
filler sounds and stutters are removed, nothing is rephrased. names can be misheard
(the analysis reads context, assessments check outside sources). how →
More from Alok Gupta
Disclosure
DoorDash aims to offer white-label infrastructure services modeled after AWS
“I think we would like to think of ourselves as an infrastructure company. That's right. Where we build products and services to help us in the things we're trying to do, but ultimately we get them to a stage of maturity and robustness through experimenting on …”
Alok GuptaFeb 1, 2021▶ 3:02Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
Insight
Problem framing is the hardest part of the machine learning lifecycle
“I think right at the start of a project is probably, and probably the hardest and most impactful part of the life cycle of the model. I think I prefer to call it sort of data-driven software because it could ultimately be it could be something other than a mod…”
Alok GuptaFeb 1, 2021▶ 4:08Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
Disclosure
DoorDash commits raw training scripts instead of pickled machine learning models
“Instead of building a model and pickling it or whatever a conversion package you want to use, we commit the actual training script to our model library.”
Alok GuptaFeb 1, 2021▶ 7:42Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
Disclosure
Deploying ML models to production at DoorDash requires data science approval
“It is perfectly acceptable for anyone at DoorDash to Build a machine learning model, but if they want to put it into production, they need approval or a review from someone like a data scientist or machine learning engineer.”
Alok GuptaFeb 1, 2021▶ 17:45Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
Insight
Training dedicated models for distinct cohorts beats fitting general models
“If there's a strong enough use case for a different cohort or segment like new users, typically it'll make more sense just to train a new model rather than trying to shoehorn it into a general model.”
Alok GuptaFeb 1, 2021▶ 22:56Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
Disclosure
Grocery expansion turns DoorDash from a three- to four-sided marketplace
“The food delivery is a three-sided. You're right. There's the merchant, the consumer, and the dasher. As we start to branch out into grocery delivery, convenience delivery, it becomes a four-sided where we introduce a picker as well.”
Alok GuptaFeb 1, 2021▶ 1:11Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
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