username4249296
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Hi

In few weeks I will be choosing modules for my third year of maths. I want to do master in ML after my undergrad and I'm thinking which modules should I take next year.

I've already decided to take ones about bayesian statistics, algorithms, strictly about machine learning and few more stats/applied modules but I'm wondering which one of these would be more useful for ML - survival analysis or graph theory?

I know the lecturer that does analysis is very good and I like stats but graph theory seems more applicable for anything related to cs (+ I took only few pure modules which I enjoyed). Any advices?

cheers
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Gregorius
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(Original post by mk1u17)
Hi

In few weeks I will be choosing modules for my third year of maths. I want to do master in ML after my undergrad and I'm thinking which modules should I take next year.

I've already decided to take ones about bayesian statistics, algorithms, strictly about machine learning and few more stats/applied modules but I'm wondering which one of these would be more useful for ML - survival analysis or graph theory?

I know the lecturer that does analysis is very good and I like stats but graph theory seems more applicable for anything related to cs (+ I took only few pure modules which I enjoyed). Any advices?

cheers
If you're intending to go on to machine learning, then survival analysis is more likely to be of direct use to you. Graph theory is relevant in CS, but it tends to be used on the more theoretical side of the subject, and for practical applications, the graph theory used is not too deep; you should be able to pick it up as you need it.
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