warning icon QCon New York 2020 has been canceled. See our current virtual and in-person events.

Predictions

Past Presentations

Engineering Systems for Real-Time Predictions @DoorDash

Today, applying machine learning to drive business value in a company requires a lot more than figuring out the right algorithm to use; it requires tools and systems to manage the entire machine learning product lifecycle. For instance, we need systems to manage data pipelines, to monitor model...

Raghav Ramesh Real-Time Predictions @DoorDash
Time Predictions in Uber Eats

Uber Eats has been one of the fastest-growing meal delivery services since its initial launch in Toronto in December 2015. Currently, it’s available in over 40 countries and 400 cities. The ability to accurately predict delivery times is paramount to customer satisfaction and retention....

Zi Wang Leading the Machine Learning Engineering Work for Time Predictions @UberEats

Interviews

Raghav Ramesh Real-Time Predictions @DoorDash

Engineering Systems for Real-Time Predictions @DoorDash

QCon: Can you describe the machine learning platform you have leverage at DoorDash?

Raghav: We built our system around common machine learning open source libraries in Python like SciKit-Learn, LightGBM, and Keras. We have a microservices architecture also built in Python which includes a prediction service that handles all the predictions and a features service. All the services are hosted on AWS.

Read Full Interview
Zi Wang Leading the Machine Learning Engineering Work for Time Predictions @UberEats

Time Predictions in Uber Eats

What is that focus of your work today?

I’m currently leading the time prediction area for UberEats. As you can imagine, precise predictions are keys for the system’s efficiency and reliability. The features I’m working on are like predicting how long it will take to deliver the food to the eater, how long will the restaurant spend to prepare the food, etc....

Read Full Interview

Less than

0

weeks until QCon New York 2020

Registration is $3055.00 ($0 off) for the 3-day conference if you register before Dec 31st
SAVE YOUR SEAT