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Analytics seems more stats oriented. Actually, I'd say the same about machine learning, too. Not that math and stats are fundamentally distinct, but there are d

• cageface 16y ago
  That's a good point. I've also considered a stats focus. My limited experience with ML suggests that linear algebra is pretty important too but certainly statistics is fundamental to both.
  • _delirium 16y ago
    For ML, I think it depends heavily on what you want to do. If you want to develop new algorithms, prove theorems about them, etc., there is a heavy math focus, although in terms of departments, you'd probably be more likely to do it in a CS department with a strong ML group, than in either a math or stats department. If you want to use ML though, the skills are quite different. A good handle on statistics is still necessary, so you know when to use which techniques, and how to interpret the results, but a lot of the math used in ML as a research area is used mainly to develop the algorithms and prove theorems about them, and isn't as relevant if you're looking at them mainly as predictive modeling or data-mining tools to apply to various domains.