
Ask HN: Is it important to have sharp math knowledge for deep learning? - thiago_fm
So I&#x27;ve been learning deep learning from Andrew Ng courses and it&#x27;s great. I actually remember a lot of algebra and calculus, as I used to be a TA in uni, but almost 10 years have already passed and I&#x27;m not that sharp anymore. For instance, I have to frequently review how to transpose a matrix, review derivate tables etc.<p>Is it worth to really review everything and do people that do deep learning professionally have always amazing knowledge about math, or is it normal to dig it up when you need it?<p>I could buy some books and go through them, but I&#x27;m not sure if it&#x27;s worth the time given that I can invest on learning all the ML&#x2F;DL things I don&#x27;t know, which are many.
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codingslave
Depends, itll probably help to get hired. If you are in a highly applied
position, probably better to know different network architectures, and why
they work in specific ways. For instance, Restnet versus VGG16, what was the
innovation? Which optimizer might be better for the two? When to slow learning
rate, when to speed it up? Theres an art to tuning and getting neural networks
to work that goes beyond mathematical understanding. But some positions may
require their employees to understand the archaic math behind machine
learning, down PCA and its relationship to eigenvectors, methods of non
differentiable optimization, etc

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sgillen
My honest advice. If you don’t already have a really good understanding of the
math I recommend you focus on the more applied stuff (like everything coding
sleeve mentioned). I fear many of the roles that actually would require you to
review the math might be looking for PhDs or similar.

You probably should at least know how to do the basic stuff in numpy or
whatever though.

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thiago_fm
Alright, that I can do. I meant more, that there is a big difference between
knowing everything by heart and comprehend everything easily and having to
look it up and stare at some formula a bit. Math is a rabbit hole, like, you
can do integrals, then line integrals, triple integrals and it goes on.

For me it isn't also very clear until where it is useful to learn math.

I'm also more on the practical/software engineering side, so I don't even have
intentions of doing research. I just want to follow the most up to date
methods.

