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Statistics and probability (up to an undergraduate level) are necessary if you want to work in machine learning. Category theory is nice (but not necessary) if
by pw0ncakes 17y ago
Statistics and probability (up to an undergraduate level) are necessary if you want to work in machine learning. Category theory is nice (but not necessary) if you want to understand the underpinnings of Haskell.
What I think really makes math generally useful, though, is that, at its root, mathematics is a formalization and generalization of problem solving. That is what formal systems and computability theory, for example, are actually about: how, in general, problems are solved.
- stcredzero 17y agoGood stats can also be very useful for metrics and project management.
- rgoddard 17y agoWhat I also find useful is getting practices with bottom up approach. In math the way ideas are developed and presented are first with the low level definitions and axioms, and then from there using logic those ideas are combined to prove more complicated theorems which can be used to solve other problems more easily. Similar to how programs can be built starting off with the low level details and then building abstractions on top of those to make dealing with other problems more easily. This skill in and of itself is useful regardless of the type of application one develops and how much actual math a problem needs.