Message from @ThisIsChris
Discord ID: 395059692503564298
AI, I think.
@Why Tea I do some at work and did some for my degree
Do you ? @Why Tea
Cool. I've been reading some on coding it. My employer (big big company) is a huge player in it, but I'm not involved in it at all at work.
Is this a good place to start (sure looks like it) and what other resources do you think are worth looking at?
@Deleted User Yes, one way / model of dealing with AI.
@Why Tea what resource to use and what to focus on depends a lot on what you're actually working on.
Are you doing some sort of image or signal processing? If so then yes Neural Networks sounds good and that site is a good start.
But Neural Networks aren't useful for every problem (though some academics are trying to push the idea that they are) so step one I would ask are you absolutely sure they are necessary for your work.
You can tell what machine learning things to focus on by laying out what type of inputs and outputs you are doing. The dimensions your data can fit are usually sequential vs non-sequential (i.e. a sentence is a sequence of words, an image is just a single vector of numbers) and categorical/symbolic vs cardinal vs ordinal.
Right, right. Thanks. But I'm not working on anything *specific* yet, as I'm trying to learn.
Of course one of the best ways to learn is to pick a thing you'd like to do, and try to solve the problem, but I'm not there yet.
@Why Tea in that case the best and most useful I've used and recommend is this one https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/
Excellent, thanks!
I love the MIT courses that are available.
MIT open courseware on Artificial Intelligence
You're welcome, yeah they are great
I’ve also heard good things about the Coursera online courses for this.
I took a Coursera course in Data Analytics learning R and they did a better job than Texas A&M’s graduate class on the same topic (I took both).
Yeah Coursera's first course was a pretty good Machine Learning Course by Andrew Ng, but last year they changed the format of the Coursera website SO MUCH that I now find it virtually unusable. That's partly by design, they give very little away for free anymore and they tightly restrict when materials are available.
So just pay for it.
That probably works for some people, but ever since after I finished school I usually study a subject in spurts in a way that doesn't fit well with Coursera's pricing model. I say this as someone who has paid for their courses and generally didn't get my money's worth before they expired.
The best experience I had with a paid Coursera course was when I was doing a programming course with other people. I feel like that model works best for Coursera because that's closest to the classroom model they are going for
When I study on my own though, I like to dive deep into something in a few goes when all of a sudden a few spare hours open up. Coursera is not conducive to this though. Courses start periodically so if it doesn't happen to be the first week of their course then you are SOL. And then the longer courses they have roll out the course material one week at a time, preventing a dive in.
That's why I like to just have all the course materials available at once, all the time. I don't think Coursera has that model for any of the courses I was interested in though.
I do some machine learning light for work and have a masters in data science from Berkeley
I can answer basic questions
It's a lot of hype concealing a clever compilation of basic techniques but a very powerful concept once understood.
It's most useful applications involve large datasets. Currently there are innumerable opportunities for application. The limiting factor is usually expertise and leadership buy in.
Even still one of the most widely applied machine learning techniques is linear regression.
This fact reveals the simplicity at the core of the concept.
Its a beautiful simplicity though and there is a growing library of well documented algorithms for various applications. Even still > 80% of the work is just wrangling the data and pre processing.
If you want to learn check out kaggle.com look at winning solutions for problems that interest you.
For coding I recommend "anacondas" python distribution.
Comes with lots of machine learning and data wrangling libraries pre installed.
Getting involved in a datakind.org project is another good way to learn.
Cool, thanks, @Perihelion - CA
@StrawberryArmada is a sick band
Anybody do tutoring stem in college? how practical idea to make money in college, it sounds like a good idea eventually I'm studying electrical engineering and so far in calculus one.
@Tyler Baker I made some decent side money while tutoring in college, I was charging faily cheap and networked quite a bit
It helped that I worked in the school's tutoring center, students liked my tutoring and asked for private tutoring outside the scheduled hours I worked for the school
sounds good, I was thinking about working in the tutoring center and then eventually doing private tutoring wich im sure is more of a responsibility.