Structuring Jupyter Notebooks For Fast and Iterative Machine Learning Experiments

Unlike in the software world, the term "reusable component" can be hard to apply in the modeling world. Experiments are often one-off, and not many codes were reused. If you're a clean code advocate who likes spending time refactoring every single line of code to follow the "Don't Repeat Yourself" (DRY) principle, you could easily spend too much time doing so. However, I'm not suggesting to go to the opposite of the "Don't Repeat Yourself" principle. I've seen very messy and unorganized Jupyter notebook directories.