Episode
Unraveling the Complexities of Model Deployment in Dynamic Marketplaces - ML 151
- Published
- May 9, 2024
- Duration seconds
- 4025
- Processing state
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Summary
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 Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Deeksha Goyal LinkedIn: Michael Sun Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .