41–50 of 56 posts
Earlier quoted context omitted.
Yes, deep learning is what web-development was twenty years ago (and now everybody and their mother can build a website).
Too bad ML as a service is already largely cornered by $FANG
Wat?
Neither Facebook nor Netflix offer outsiders access to their ML platform, and you completely forgot Azure, which IMHO has the most mature offering of the big 3 in this space.
These guides pop up left and right, lately. I can't comment on their quality (I assume it's somewhat decent) but it's kinda ridiculous to try compressing a college degree's worth of knowledge into a bunch of sleek online tutorials.
> it's kinda ridiculous to try compressing a college degree's worth of knowledge into a bunch of sleek online tutorials. Honest question, why? We used to give degrees (albeit hundreds of years ago) for material that now is covered, at a high level, in a single course (e.g. physical sciences). The amount of material to cover, and to master, increases dramatically over time. It makes sense to compress the knowledge to…
why would every ML guide use cats as example
Earlier quoted context omitted.
> it's kinda ridiculous to try compressing a college degree's worth of knowledge into a bunch of sleek online tutorials. Honest question, why? We used to give degrees (albeit hundreds of years ago) for material that now is covered, at a high level, in a single course (e.g. physical sciences). The amount of material to cover, and to master, increases dramatically over time. It makes sense to compress the knowledge to…
Not OP but I suspect they will say something about the math behind it. It's very true you can get quite adept at plug-and-play machine learning models (and indeed be quite successful) but the theoretical statistics, linear algebra and overall mathematical maturity take a long time to develop in my opinion.
One of my random question is that what does Google gain by spending resources on developing course like this? Do they want more people to do machine learning as there is a short age of developer with this skill in the market or is there something else involved in the mix? Secondly, for some reason data science just doesn't excite me as much as typical software development goes. Like, why am I not excited enough to go…
Consider a larger organization (1000+ people perhaps), if groups within that org can train their people with these materials or even send them to Google to be trained in this subject matter they can come back with a nice shiny credential. Whether that ultimately becomes useful to that individual or the group is up to them but really it helps google foster that relationship with the main organization to eventually snag higher contract values.
That probably made no sense, but I thought I'd give my two cents (however crummy they might look).
Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
Honestly, unless these ML bootcamps are extensive courses on calculus, linear algebra, and statistics and not just "Here's k-means. Memorize it" I doubt they'll harm the market for grad school educated data scientists.
I completely understand why there is such a stigma around bootcamps. Nobody can deny that they don't afford the same depth that you'd get at a "real" program. But they can be amazing for career switchers like me, who had no real direction in college. Don't look down your nose at them.
One of my random question is that what does Google gain by spending resources on developing course like this? Do they want more people to do machine learning as there is a short age of developer with this skill in the market or is there something else involved in the mix? Secondly, for some reason data science just doesn't excite me as much as typical software development goes. Like, why am I not excited enough to go…
By all means, keep at it! Better to be an exceptional backend dev than average ML engineer. No one can predict the future anyway. It's certainly possible that the ML job surge is gonna stop abruptly when most of the advances have been captured by APIs.
Earlier quoted context omitted.
The idea of my approach was that a "power user" could add the rules and scores without having to understand something that may take a while to explain. A scoring sheet can be displayed for a given message that would make sense to just about anybody with an associate degree. Example scoring sheet for a given message: Category: Spam Rule-ID Score ---------------- NgrPrnc1 7 bPills 5 knownPeople -3 Total: 9 Threshold Ex…
This is how people did things back in the time. "Expert systems" with hand-crafted rules, built by "experts". From the past, we learn that these systems are brittle and break continuously. For example, what happens when spammers start using different words, or send legitimate looking emails that are actually spam? Do you think you can build rules to catch 70%, 80%, 90% or 99.99% of spam? If your goal is simply showin…
But what I described had additional purposes such as sub-routing to various departments. It was a multi-purpose email categorizer in the early days of spam. Each approach has trade-offs. I'm not sure how you'd apply a "decision tree" using weights in a way that makes sense to a power user. A non-weighted decision tree seems too blunt an instrument. One generally needs multiple "clues" (factors) voting in tandem.
Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
You cannot learn machine learning or deep learning in a few months. You can learn to copy what these guides do, but if you want to do something slightly different you will feel you know nothing (because you actually probably don't know anything about the maths behind why the things works, so when you want to change them you don't know how)
Of course understanding the theory will be helpful in knowing which architectures are most likely to be productive and what-not, but this whole field is very empirical anyway. So if your experimenting is a little less guided my intuition rooted in theory, that's not exactly the end of the world.