Very company dependent. At Luminoso (http://luminoso.com), we live in Python, with varying doses of Javascript for frontend, very little R (but some of us know it), Java and C++ are pluses (for working with other people's software), and we have at least some Haskell in production (mostly for preprocessing). And plenty of ops tools for deployment. We have used a few neural networks frameworks and machine learning packages; definitely the Python machine learning ecosystem is big for us but we haven't found our One True neural network framework yet. Other companies (say in image recognition, Ditto Labs for instance) are definitely more CNN-oriented, yet others are certainly doing work in R.If you have a company that is doing genuinely interesting AI work, it's likely that they are somehow on the forefront of research, pushing existing tools to do things that they can only barely do. If you find yourself in an AI role (typically only some roles actually do AI, of course -- systems need to stay up, great UIs need to be built, etc.), I would guess that you'll need to familiarize yourself with their particular toolsets and methods rather than assuming that there are universally correct things to go learn.
hazard|9 years ago
sua_3000|9 years ago