Tinkering with new languages is fun and worthwhile to a point, but I honestly feel that my time is now better spent learning new problem domains. Languages matter, but the less tangible skills I've developed working across different domains have been more valuable and fundamental. The things I've learned while studying Machine Learning and DSP over the last year are much more broadly applicable than I would have guessed.
When you start to think of any stream of numbers as a digital signal, a lot of the techniques become useful. For example, user interfaces provide a fairly high-resolution stream of quantifiable user events, like touch positions. Often you want to smooth these in specific ways. If you understand how a low-pass filter works, this is easy.
Any tips on where / how to start? Which books / tutorials worked for you? My background is in software engineering and the only thing I know about DSP is a very very basic understanding of the Fourier transform :)
