As mentioned, machine learning models produce extremely different results depending on the training data you use, the choices of parameters, and the input data. It is essential to be able to reproduce results for collaborative, creative, and compliance reasons:
- Collaboration: Despite what you see on social media, there are no data science and machine learning unicorns (that is, people with knowledge and capabilities in every area of data science and machine learning). We need to have our colleagues' reviews and improve on our work, and this is impossible if they aren't able to reproduce our model results and analyses.
- Creativity: I don't know about you, but I have trouble remembering even what I did yesterday. We can't trust ...