Solving the Real Issues with the MLflow Team - ML 059

If you’re looking for a team that actually cares about the issues you’re facing, look no further than Databricks, and they’ve got something exciting out. In this episode, Michael and Ben welcome on the development team of MLflow, an open-source lifecycle manager for machine learning. They cover how Databricks is redefining how developers and engineers collaborate, the reason behind Databricks’ crazy success, and the number ONE most important testing structure for any development team. “A lot of the success was attributed to process and dedicated focus on the interface, understanding what major problems we were going after. ” - Corey Zumar In This Episode How Databricks allows data analysis, engineers, and developers to collaborate effectively Why Databricks was able to rake in 800,000 downloads per MONTH in their first year A simple but powerful methodology that helps Databrick identify the highest ROI problems to tackle (not just the most popular ones) The number one MOST important testing structure that reveals how Databricks keeps their work top-notch What makes Databricks unique from everyone else and is the KEY to putting users first in 2022 Sponsors Top End DevsCoaching | Top End DevsSpecial Guests: Corey Zumar, Harutaka Kawamura, Weichen Xu, and Zhang Jin.Sponsored By:Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your DreamsTop End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.