Re:Ask HN: As a data scientist, what should be in my toolkit...
by dsacco on Tuesday February 20, 2018 @02:01PM
(#16422979)
Sure, I agree. Abstract algebra isn’t directly helpful. But:
1. The context is knowing more math than someone who has an undergraduate degree in it,
2. Abstract algebra is part of such a degree, and contributes significantly to overall mathematical maturity, and
3. You can avoid some subjects in the short term, but in the long term you can’t progress further without a reasonable mastery of algebra and analysis.
Probability theory and linear algebra are heavily used in data science. You won’t be as competitive a candidate for a job if you don’t have a firm grasp of both subjects. At a certain point, linear algebra ceases to be distinct from abstract algebra, and those exercises you were doing become applicable to real world results.
1. The context is knowing more math than someone who has an undergraduate degree in it,
2. Abstract algebra is part of such a degree, and contributes significantly to overall mathematical maturity, and
3. You can avoid some subjects in the short term, but in the long term you can’t progress further without a reasonable mastery of algebra and analysis.
Probability theory and linear algebra are heavily used in data science. You won’t be as competitive a candidate for a job if you don’t have a firm grasp of both subjects. At a certain point, linear algebra ceases to be distinct from abstract algebra, and those exercises you were doing become applicable to real world results.