Modern, Principled Data Science Workflow || Eric Ma

Suppose you are starting a new data science project (which could either be a short analysis of one dataset, or a complex multi-year collaboration). How should your organize your workflow? Where do you put your data and code? What tools do you use and why? In general, what should you think about before diving head first into your data? EVENT:
PyData Boston SPEAKER:
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Original video source: https://www.youtube.com/watch?v=Dx2vG6qmtPs **** Love Python? You will love Kite! Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite for 6 months and I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=codingtech&utm_content=description-only https://www.youtube.com/watch?v=kETDOnnt5sc