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You don't need graduate level math, but if you want to use machine learning it's basically mandatory to have a solid understanding up to calculus, linear algebr

by rm999 14y ago

You don't need graduate level math, but if you want to use machine learning it's basically mandatory to have a solid understanding up to calculus, linear algebra, and probability/statistics. At least if you want to understand the underlying algorithms, which in my opinion is essential to being a good data scientist. I did a masters in machine learning/computer science, but I think I could have learned a lot of the stuff on my own. The value of the masters was in projects, interaction with professors/other students, and the ability to do research (which I think is very underrated). FYI: a lot of jobs will discriminate against people without technical degrees and graduate degrees. Independent projects or relevant work experience will help. My career predates kaggle, but I did do a machine learning competition to practice and apply my knowledge. Winning these will look good on a resume, but only to a point: there's a lot more to being a data scientist than what these competitions test.

up_and_up 14y ago
> FYI: a lot of jobs will discriminate against people without technical degrees and graduate degrees. Thanks for the info. Thats my dilemma I guess. Leveraging free online resources can only take you so far. I guess my assumption was that I needed to get a masters and I was wondering which field made the most sense: Applied Math / Stats / CS. At this point it seems like CS would be the way to go.
- rm999 14y ago
  CS would give you the most bang-for-your-buck, especially a program that can let you specialize in machine learning. You may be able to leverage your software engineering positions to skip an additional degree. I've heard people argue that data scientists are software engineers with additional specialized knowledge, which I think is largely true.
Cyranix 14y ago
> You don't need graduate level math, but if you want to use machine learning it's basically mandatory to have a solid understanding up to calculus, linear algebra, and probability/statistics. At least if you want to understand the underlying algorithms, which in my opinion is essential to being a good data scientist. Key word in that last phrase being good. There are, of course, companies which will take developers with little experience and try to mold them into machine learning experts without much support -- the end result being misguided application of techniques. But hey, it's a job...

by rm999 14y ago

up_and_up 14y ago

> FYI: a lot of jobs will discriminate against people without technical degrees and graduate degrees. Thanks for the info. Thats my dilemma I guess. Leveraging free online resources can only take you so far. I guess my assumption was that I needed to get a masters and I was wondering which field made the most sense: Applied Math / Stats / CS. At this point it seems like CS would be the way to go.

rm999 14y ago
CS would give you the most bang-for-your-buck, especially a program that can let you specialize in machine learning. You may be able to leverage your software engineering positions to skip an additional degree. I've heard people argue that data scientists are software engineers with additional specialized knowledge, which I think is largely true.

Cyranix 14y ago

> You don't need graduate level math, but if you want to use machine learning it's basically mandatory to have a solid understanding up to calculus, linear algebra, and probability/statistics. At least if you want to understand the underlying algorithms, which in my opinion is essential to being a good data scientist. Key word in that last phrase being good. There are, of course, companies which will take developers with little experience and try to mold them into machine learning experts without much support -- the end result being misguided application of techniques. But hey, it's a job...