๐ค Do you know how to structure your data science projects neatly? If not, haven't you lost a file because you don't remember where it's stored?
When I first started my data science projects, I was working almost exclusively on Jupyter notebooks... As I progress in the journey, I needed to use scripts and start version controlling.
๐ง Having no structure in my projects proved to be a roadblock - it's so easy to lose track of where things are.
๐งฝ That's when I realize the importance of having a clean, planned structure for a project.
๐ง With a structure, you won't need to rely on your memory to know which file is stored in which randomly named folder anymore. It helps my mind to focus on more important things!
๐ค Having a structure makes your code more maintainable and shareable too!
Thanks a lot to Baran Kรถseoฤlu for sharing this useful structure in a blog post (modified)
(Edit) Danny suggested that we have folders to document experiments on methods and approaches too!
Bonus: cookiecutter is a python package that helps you make this structure automatically!
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