Testing Data Science Code || Eric Ma

Code written in a programming language is the most flexible way to accomplish your data science work. However, every line of code we write is technical debt. In this talk, we will go through the different kinds of tests that you might want to write when doing data science, and how you can incorporate testing into your workflow to write robust code that builds your confidence. EVENT:
PyData Ann Arbor 2019 SPEAKER:
Eric Ma PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks CREDITS:
PyData YouTube channel: https://www.youtube.com/channel/UCOjD18EJYcsBog4IozkF_7w https://www.youtube.com/watch?v=fmVbtHMHEZc