Unraveling the Complexities of Model Deployment in Dynamic Marketplaces - ML 151
Adventures in Machine Learning - Un podcast de Charles M Wood - Les jeudis
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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.SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipSocialsLinkedIn: Deeksha GoyalLinkedIn: Michael SunBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
