Submitted by sad_potato00 t3_zvnjox in MachineLearning
Hello everyone,
I'm trying to figure out how to apply concepts from SE into ML research.
For me it seems like I can find really good settings for my Model and dataset, and it can be reproduced. However, I think there's a better way to create code for experimenting. Fore example, creating and testing baselines, and logging test results seems to be the same between most (if not all) my experiments. I find myself copying and pasting a lot of code snippets between my projects. Yet, every time I try to set down and write a generic code for experimenting. I find that it's either too limiting or impossible for me to write it. I think if I looked into software engineering concepts and principles it might help.
I really want to know what was your experience in searching/applying SE into this field, or if you even think it's worth it/possible to.
some of my colleagues think it's a waste of time, specially considering that the model would run on completely different code.
Itachi_99 t1_j1qj5pt wrote
What is SE?