An algorithm to help choose the most effective or efficient algorithm

[datatalking]

First off, I'm enjoying this repo, and you have already solved a big chunk of what my team and I are in process of doing so I'm excited about contributing.

I've been looking for a process to connect algorithms and currently doing that with decision tree analysis and then pruning those based on optimization. Could we add or expand this repo with information relative to context or industry usage for these algorithms?

In many textbooks, they discuss the details in the front of the book, but the back of the book has a quick reference index, so you can look for scheduling theory and flip to chapter 9, vs. greedy algorithms on say chapter 4. The question that comes up again is whether there is a known (semi-universal) way for the user to have an assistive decision tree to choose unless they have advanced knowledge of decision theory.

Could we expand this repo to include context and industry contextual usage?

[shellfly]

@datatalking Glad to know that this repo is helpful to you. I like the idea to supply context or industry usage for each algorithm.
I'm not quite sure what's "(semi-universal) way" you mentioned look like. Could you give some specific examples on how to include this kind of information.