It's not really a question of the "correct" data. To evaluate whether an observation is anomalous, you typically define a threshold for what's considered not-normal, e.g. an observation 2 or 3 standard deviations above the mean.
This may leave you with some false positives (like any system of this nature would). Of course, you could go the route of actually defining an anomaly yourself and building a more sophisticated model (i.e. one not using z-scores as the measure of anomaly), but that's obviously a different scope.
Why not learn R? In the last year I've spent around 80% of my time working with R, coming from the last five years almost exclusively with Python, and there are some great reasons to use R. Although if the tidyverse didn't exist I'm not sure I'd be saying that. I find that suite of packages together to be a very cohesive set of tools for doing data science.
Three reasons (I know both languages well): (1) R is used much less in the data science industry, and (2) Python is a more universally useful language. If he learns it for data science then he can easily write utility scripts, build a back-end, etc. (3) the overlap between R and Python capabilities is so significant it would be a waste to start with R, I would only suggest picking it up if he needs some niche package that he can't get in python.
Not the person to whom you asked this question, but I'm also a user of TabNine. In my experience, the "recommendations" / autocompletions provided by the tool are usually very short (probably less than 20 characters on average), and I don't use it for terribly complex chunks of code. Where I like it most is in the initialization of common code chunks like `if` and `for` loops, using variables instantiated in nearby preceding lines. It figures out things like `for(customer in customers)` as I'm writing `for`.
I worked on a project that basically was a very simple rules engine, encoding a bunch of domain knowledge in a digestible dashboard format, which happened to use a few predictive models' output as well to drive a few of the rules. The product owner insisted that "AI" be in the name, whereas I was reluctant to put lipstick on that pig. Ultimately (as usually happens if the product owner is your boss) the "AI something something" name stuck, but the whole branding of the endeavor rubbed me the wrong way (even though the product was actually somewhat useful).
Yep. It may only take one or two false positives to lose a customer worth potentially orders of magnitude more than any particular item (depending on the price of the item, of course).
For context, I’m not referring to SV software engineer salary just normal big city America.
I know a guy who probably now makes a little more than I do on his main job, is my age, but has been saving and investing much more consistently.
He’s always doing side gigs for $50 - $70/hour. Which is really nothing for a software engineer even in my city and much less than he would be making as a full time contractor.
When an opportunity like that comes up for me to “make extra money”. I always turn them down even at much higher rates. Anything we can’t get with my relatively average salary and my wife working we don’t need. I enjoy my time way too much. I don’t think I would work a contract that paid the equivalent of twice my salary as a side job.
I can relate to your friend more, honestly. $50-70/hr is not an elite high level professional salary, but it’s no joke, and much more than the $0/hr you'd otherwise make farting around on HN or watching Netflix.
When you’re young and able, life is merely a race to turn time into money fast enough to allow you to survive long after you can no longer turn time into money.
Every day I waste now may translate into a week of eating dog food after I can no longer work. Therefore, I generally want to maximize the dollar utility of my time, while I can. If I could guarantee that I’d drop dead as soon as I retired, maybe I’d stop and live a little now. But since I can’t (an don’t want to commit suicide when I run out of savings), well, an extra dollar is an extra dollar!
“Money isn’t everything” -says someone with a lot of it.
This may leave you with some false positives (like any system of this nature would). Of course, you could go the route of actually defining an anomaly yourself and building a more sophisticated model (i.e. one not using z-scores as the measure of anomaly), but that's obviously a different scope.