I was wondering about machine learning/data science project structure/workflow and was reading different opinions on the subject. And when people start to talk about workflow they want their workflows to be reproducible. There are a lot of posts out there that suggest to use make for keeping workflow reproducible. Although
This post is more an invitation for a dialogue rather than a tutorial. Perhaps your solution is perfect. If it is then it will be interesting to hear about it.
In this post I will use a small Python project and will do the same automation tasks with different systems:
There will be a comparison table in the end of the post.
make is very stable and widely-used I personally like cross-platform solutions. It is 2019 after all, not 1977. One can argue that make itself is cross-platform, but in reality you will have troubles and will spend time on fixing your tool rather than on doing the actual work. So I decided to have a look around and to check out what other tools are available. Yes, I decided to spend some time on tools.This post is more an invitation for a dialogue rather than a tutorial. Perhaps your solution is perfect. If it is then it will be interesting to hear about it.
In this post I will use a small Python project and will do the same automation tasks with different systems:
There will be a comparison table in the end of the post.
