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I have a similar feeling. To learn the basic math (single, multivariable calculus, linear algebra) will probably take you 300 hours of serious study if you don’

I have a similar feeling. To learn the basic math (single, multivariable calculus, linear algebra) will probably take you 300 hours of serious study if you don’t already know any of it. That’s one hour a day for a year (if you actually succeed at studying 8 days out of 10, which is pretty good) without implementing anything. If you want to get to something like a beginner nonlinear optimization course you probably need to study proofwriting then advanced calculus first. Add in a serious undergrad probability and stats course and you’re at 2-3 years of study before you actually did anything... If you’re someone who enjoys math you might do it for its own sake but it’s difficult for me to imagine someone making serious progress in this direction without either a passion for the subject, an already relatively strong background, or being in a university.

BeetleB 7y ago
>To learn the basic math (single, multivariable calculus, linear algebra) will probably take you 300 hours of serious study if you don’t already know any of it. Frankly, compared to many other disciplines, that's pretty light. Single variable calculus, linear algebra and probability were all required in my undergrad CS curriculum. Multivariable calculus was the only extra course. And if you're in most engineering disciplines, all of this is required. I'm guessing the difference for CS folks is that they rarely use this stuff in the curriculum, whereas in most engineering programs, you'll use calculus day and night.[0] So for someone like me (engineering background), it was easy to dive into even years out of school as I'd not forgotten a lot of math. Now of course, if you want to get deep into ML, there's a lot more math than that. However, most successful people using ML do not need to know that math. And compared to other disciplines like control theory, communications theory, etc, the prerequisites for ML are a lot lighter. [0] Only in school. Almost never in industry.
the_watcher 7y ago
I agree with the overall sentiment as well. However, 300 hours of study to go from 0 to single & multivariable calculus plus linear algebra doesn't actually sound that bad. 10 hours per week (2 hours per day post work, make up missed days on the weekend) for 30 weeks?
- bigred100 7y ago
  It depends on how many other responsibilities you have or other activities you engage in, and how much you care about the project, I suppose. To me 10 hours of solid study after work is a lot, but other people might throw out some other stuff I do and be willing to spend it studying. I can’t comment on whether it’s a good idea. (I believe there is very much such a thing as too much work ethic).
  - DoctorOetker 7y ago
    For us studying physics, thats like 30 hours of actually attending class for each course, so 90 total, then some days of study, say 3 x 8h, thats more like 114h, not 300...

BeetleB 7y ago

>To learn the basic math (single, multivariable calculus, linear algebra) will probably take you 300 hours of serious study if you don’t already know any of it. Frankly, compared to many other disciplines, that's pretty light. Single variable calculus, linear algebra and probability were all required in my undergrad CS curriculum. Multivariable calculus was the only extra course. And if you're in most engineering disciplines, all of this is required. I'm guessing the difference for CS folks is that they rarely use this stuff in the curriculum, whereas in most engineering programs, you'll use calculus day and night.[0] So for someone like me (engineering background), it was easy to dive into even years out of school as I'd not forgotten a lot of math. Now of course, if you want to get deep into ML, there's a lot more math than that. However, most successful people using ML do not need to know that math. And compared to other disciplines like control theory, communications theory, etc, the prerequisites for ML are a lot lighter. [0] Only in school. Almost never in industry.

the_watcher 7y ago

I agree with the overall sentiment as well. However, 300 hours of study to go from 0 to single & multivariable calculus plus linear algebra doesn't actually sound that bad. 10 hours per week (2 hours per day post work, make up missed days on the weekend) for 30 weeks?

bigred100 7y ago
It depends on how many other responsibilities you have or other activities you engage in, and how much you care about the project, I suppose. To me 10 hours of solid study after work is a lot, but other people might throw out some other stuff I do and be willing to spend it studying. I can’t comment on whether it’s a good idea. (I believe there is very much such a thing as too much work ethic).
- DoctorOetker 7y ago
  For us studying physics, thats like 30 hours of actually attending class for each course, so 90 total, then some days of study, say 3 x 8h, thats more like 114h, not 300...