Predictions
Presentations
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....
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...
Interviews
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.
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