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Need advice about how to evaluate your proficiency #11
Need to tell people how they know they're out of the Danger Zone or how they know they are hire-able.
I need some review!
I added a section warning people about the "Danger Zone" (when you know enough to throw some algorithms at some things, but you don't have enough knowledge, science, or stats knowledge to be an expert). The "danger zone" is familiar to anyone who's taught themselves something really big. [Here's the section.]
What's missing: some advice! It would be nice if the guide could say something besides, basically, "It's hard."
Well, a user on Hacker News was kind enough to give a suggestion today. I put a quote from them on this branch because I'm hoping for some review. If it looks like a good thing to include, maybe I'll paraphrase.
I'm wary of making false promises or saying "well just do this and YOU'RE ALL SET," but it does sound like some sound advice honestly. So maybe after paraphrasing into a more cautious/conservative tone, it will be good.
Kaggle competitions are a so-so way to practice ML. I have ethical issues with Kaggle because I think they're exploiting researchers to build products for companies, but that's a conversation for another day.
One good way to have your work double-checked is to post it on Cross-Validated: http://stats.stackexchange.com/
There's some really smart people on there that will give you great advice.
There's also some great online communities like Hacker News, reddit.com/r/DataIsBeautiful, /r/DataScience, and /r/MachineLearning where you can post your work and ask for feedback. I've learned a ton this way, and it really helps you practice dealing with feedback on your week (which is an often-underpracticed skill).
I think the best advice is to tell people to always present their methods clearly and to avoid over-interpreting their results. Part of being an expert is knowing that there's rarely a clear answer, especially when you're working with real data.
Thanks for the thoughtful response @rhiever.
I hadn't thought about Kaggle that way, as an outsider looking in ... I work in InfoSec and being so used to bug bounties and the like, the premise didn't shock me. But this is a good perspective to hear.
So your suggestion is rather to:
And repeat, of course. This makes a lot of sense. I'll mull this over a bit and try to add a clear, succinct section to the guide.
I don't think I can paraphrase this better than you've said it. Can I quote you? Alternatively, I could do this first PR (about the practice-review-fix approach), then you could use your own words and submit a PR. Or just quote. LMK.