Sometimes it really does suck to not know what you don’t know. Having no college math education I didn’t know what I needed to know to be on par with what math undergraduates know. The further I make it into my self selected MOOC courses meant to stand in for a C.S degree the more I realize where I am lacking and what I need to do to fix it. If I really want to put my money where my mouth is and do research I’m gonna need to go pretty deep into math I’ve been avoiding.
Coding MOOC’s try to do their best to offer their courses to anyone, even the people with little to no experience in math, hence Andrew Ng in his ML class brushing over all the math in that course. I appreciate it as somebody who doesn’t know math at that level and still wants to learn ML pragmatically, but the brutal truth is without rigorous understanding I will only be able to use research. Not contribute to research which is my goal. So I almost feel like I am starting at square one again staring at the mountain of what I need to know ahead of me. Wishing I started sooner but trying to not be hard on myself, while mentally shifting my timelines and trying to find the best math resources. I found some goodones though.
I know it’s better to figure out I’m doing something wrong and correct it, but man I wish studying was quicker and easier. Oh well, I was planning on doing this the rest of my life anyway, what’s a little added time to make sure I get it right?
For me, reading Quantum Computing Since Democritus was the moment when I realized I barely know anything. The author mentions dozens of topics in passing, some of them I do not understand, some of them I understand enough to know that he is not bluffing. It would take me at least five years of full-time studying to get on the level where I would understand everything mentioned in that book—and of course that is very unlikely to happen, because there are many other things to do.
Sometimes it really does suck to not know what you don’t know. Having no college math education I didn’t know what I needed to know to be on par with what math undergraduates know. The further I make it into my self selected MOOC courses meant to stand in for a C.S degree the more I realize where I am lacking and what I need to do to fix it. If I really want to put my money where my mouth is and do research I’m gonna need to go pretty deep into math I’ve been avoiding.
Coding MOOC’s try to do their best to offer their courses to anyone, even the people with little to no experience in math, hence Andrew Ng in his ML class brushing over all the math in that course. I appreciate it as somebody who doesn’t know math at that level and still wants to learn ML pragmatically, but the brutal truth is without rigorous understanding I will only be able to use research. Not contribute to research which is my goal. So I almost feel like I am starting at square one again staring at the mountain of what I need to know ahead of me. Wishing I started sooner but trying to not be hard on myself, while mentally shifting my timelines and trying to find the best math resources. I found some good ones though.
I know it’s better to figure out I’m doing something wrong and correct it, but man I wish studying was quicker and easier. Oh well, I was planning on doing this the rest of my life anyway, what’s a little added time to make sure I get it right?
For me, reading Quantum Computing Since Democritus was the moment when I realized I barely know anything. The author mentions dozens of topics in passing, some of them I do not understand, some of them I understand enough to know that he is not bluffing. It would take me at least five years of full-time studying to get on the level where I would understand everything mentioned in that book—and of course that is very unlikely to happen, because there are many other things to do.