Unraveling the Complexities of Model Deployment in Dynamic Marketplaces - ML 151
Update: 2024-05-09
Description
Deeksha Goyal is the Senior Machine Learning Engineer at Lyft and Michael Sun is the Staff Software Engineer at Lyft. They delve into the intricacies of machine learning and data-driven technology. In this episode, they explore the challenges and innovations in deploying models into production, particularly focusing on the real-world implications of ETA (Estimated Time of Arrival) modeling at Lyft. They share valuable insights, from the complexities of A/B testing and long-term impact assessment, to the dynamic nature of handling real-time data and addressing unpredictability in route predictions. Join them as they journey through the world of model deployment, bug identification, and career development within the fast-paced environment of Lyft's data-driven infrastructure.
Sponsors
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Sponsors
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Comments
In Channel
Download from Google Play
Download from App Store
United States00:00
00:00
1.0x
