Solving the Real Issues with the MLflow Team - ML 059
01.27.2022 - By Adventures in Machine Learning
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
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Special Guests: Corey Zumar, Harutaka Kawamura, Weichen Xu, and Zhang Jin. Sponsored By:
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