[tibbon]

Fair enough. I've hit a sweet spot now in having done Ruby for ~8 years, so I can get away with saying, "having someone else deal with the front end. I just want to talk about data".

The new problems I'm working to learn to solve are with ML, NLP, etc. I'd like to step away from web services completely soon, and just live completely with data.

[gettersetter]

I am curious, how did you transition into ml, nlp. I am thinking of transitioning to ml, as work is getting kind of boring for me, but most job requires at least a master in the relevant field. I am self studying right now, maybe going back for a master, but I felt I lack alot of necessary probability and linear algebra theorems. I can code svm, neural network from nothing. I understand basic markov chain, bayes network, but that is really just scratching the surface. Any recommendations?

[thomasahle]

The 2016 ml scene doesn't seem so different from the 2016 front-end wild west I gather from this thread. Unfortunately. Machine Learning is in rapid flux, the solid theory of svm and the like are getting abandoned for a lot of techniques that seems to work some times. Certainly some people have a very good intuition for what works, and how to make it scale, but there is no one authority and you have to keep constantly up to date.

[choicewords]

I'm in the same boat. I'm no longer interested in the plumbing, much more the type of questions that can be answered with large scale data, and other types of efficiencies that are dormant with 'pure' code.