> background in linear algebra, probability, calculus
Curious. What does 'background' mean in this sentence. You can spend years studying just one of these in depth. How much is "enough" for ML?
Re:Deep Learning Course
by pedrosorio on Sunday November 19, 2023 @04:03PM
(#38337976)
The basics. 1 semester course for each.
thanks!
I wonder if someone has compiled a resource with just enough math for ML.
I believe fast.ai does this - they start with you using real tools and teach you the foundation as it becomes relevant
Re:Deep Learning Course
by patrick451 on Sunday November 19, 2023 @05:47PM
(#38339318)
I'd say slightly more. Maybe it's just because I attended a state school, but I think my first semester calculus class was all single variable (20 years ago now, so my memory is rusty). You really to understand gradients and jacobians for ML, which I think was calc III for me. But you can skip curl and div part I guess.
Re:Deep Learning Course
by pedrosorio on Monday November 20, 2023 @11:44PM
(#38359367)
Oh, that’s right. Multivariable was Calc II for me so technically two semesters.
how much of that do you really use for ML
Re:Deep Learning Course
by CamperBob2 on Wednesday November 22, 2023 @12:28PM
(#38382154)
Not much of your calculus book will be relevant beyond the first couple of chapters, but you'll live and die by the numerical-method sword. The idea is that you need the analytic insight from the former to understand the latter.
I don't know if I really buy that, though.
I’ve taken uni level courses for all of that but it’s been… 15+ years and is entirely out of my brain. I appreciate the feedback. Sounds like I need to brush up and I appreciate your point about it being a mathematical concept at its foundation
If you're not interested in learning these areas, it's also safe to say you aren't really interested in deep learning either. Which is not to say if you don't already know these areas you aren't interested in deep learning, but if you don't know them and are interested in deep learning you're likely already studying them.
I say this because deep learning and the vast majority of ML really just boil down to an application of these basic tools. Deep learning/ML without the linear algebra, probability theory, calculus and coding isn't really anything at all.