[kradroy]

I disagree with you. Both ways work. Starting from theory, or starting from practice.

However, in a business setting, starting from practice is much more effective. As a lead dev and a manager who's had over 20 years of experience in AI/ML I've trained several engineers in building ML systems.

I always start with a business problem and point them to resources (frameworks, blogs, jupyter notebooks) to help them along. The problem is small enough for them to solve in less than a quarter. I avoid micromanaging them and will only answer larger questions by providing more resources. If they really get stuck I'll sit with them and walk through the issue. I have yet to have an engineer be unable to 1) get a model working and 2) tune it to production quality.