Podknife - Solving the Real Issues with the MLflow Team - ML 059 by Adventures in Machine Learning

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Solving the Real Issues with the MLflow Team - ML 059

Podcast |: Adventures in Machine Learning
Publisher |: Top End Devs
Media Type |: audio
Podknife tags |: Artificial Intelligence,; Business,; Careers,; Interview,; Machine Learning,; Technology
Categories Via RSS |: Business,; Careers,; Education,; How To,; Technology
Publication Date |: Jan 27, 2022
Episode Duration |: 00:48:34

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

Special Guests: Corey Zumar, Harutaka Kawamura, Weichen Xu, and Zhang Jin.