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I am a long time developer who is trying to move into data science / ML. What I've found after taking off for 12 months of self-study, is that it quickly dissolves into you must know math . As far as I can tell, its take a problem, map it into a vector space, then use the full power of mathematical analysis on it . There is a huge push by large companies to make AI as a service though, and for that, you only really n…
Earlier quoted context omitted.
Was your undergrad in computer science or did you 'hop' into the masters?
Liberal arts troll reporting. Starting my prereqs for a masters in CS this summer. It'll take me quite a bit longer to complete than someone who started with a BS in CS (basically I'm taking enough undergrad courses to fill several semesters, before even getting to MS work). However I was a developer for several years before this leap, and I feel pretty comfy with math things. Also working on reproducing papers to de…
Anyone here have any good book recommendations?
It does require matlab though.
Whenever I encountered something I didn't know, I googled around until I had even a vague idea.
That said a) I don't know how do-able that would have been without the math background I've already got, and b) I haven't gotten much further in that reading that one paper ...yet.
Regarding the math - The only thing I know for sure to point you at is multivariable calculus, which is also (probably) the most useful math class I ever took. (It helps that the teacher was completely amazing). The set of concepts it introduced me to are amongst the most useful things I ever learned, and it's that understanding that has always given me a leg up on jumping into things at the deep end.
(I took multivar from UC berkeley in, I think, spring 2002? I went looking for video lectures, but did not find what I was looking for...)
I did Udacity's Deep Learning and Machine Learning courses and found them to be a really great introduction, and enough for me to continue on my own. I'm not a front-end dev, but also definitely not a mathematician or computer scientist. You should be able to learn enough to do some cool stuff. - Make sure you know Python well - pretty much everything interesting in ML is in Python. If you already know JS this should…
In Feb 2015 I quit my job as a front end developer to learn more about machine learning. First, I went through the Recurse Center, which is a 3 month program sort of like a writing retreat for programmers. I learned a lot about Python and AWS in that time, and got an internship as a data engineer. In that Fall, I started a computer science master's. I've taken mostly courses in machine learning including: Machine Lea…
I work in machine learning and I don't think a 3 months course is going to transform you in a machine learning engineer. I think you need at least the time you took. You need to learn the maths, statistics, etc. Apply those tools to real problems, get some experience with different problems and techniques. And, finally, be involved in some type of research. Because machine learning is evolving so fast, you need to le…
That is VERY different than what 99% of people should be doing with ML which is: Spinning up some K80s on Azure, installing TF/CUDA/OpenCL, pulling existing pre-trained models off the shelf, and running inference on a novel data set.
That's how you get into it as a garden variety dev.
Otherwise, go for the PhD if you want to actually make new stuff.
Dan Shiffman created a Youtube playlist titled "Intelligence and Learning", which might be a good place to start. This is the link to his channel https://www.youtube.com/user/shiffman