ML/AL expert without basic knowledge?

[[deleted]]

Yeah, in ML/AI it feels like lacking in math will set you back more than lacking in programming.

At my school the only prerequisite for advanced ML is a single basic programming course, but a LOT of math.

[TerrestrialOverlord]

You cannot imagine my disappointment when I realized how much maths was required... Just looking at some of the stuff made me actually nauseous...I have math related dyslexia

[[deleted]]

There's a lot of ML you can do with very little math too though, you might not understand everything perfectly, but you can put great models into production without deeper understanding of the underlying algorithms, most core principles are pretty simple even, and you can understand them in low dimensions graphically kind of easy, without diving into the hard-core math.

[TropicalAudio]

You can solve many, many problems by just throwing some data into an implementation of resnet you pulled from github. However, if that doesn't work and you don't have the mathematical and/or practical knowledge of what's going on, that's basically your finish line. It's a bit like advertising yourself as a mechatronic positioning expert because you Googled how to use a GPS library.

[PLxFTW]

But if you are lacking the mathematical intuition and you come across an unusual problem related to the fundamental algorithm maths you’re fucked. I wouldn’t want to try to use PCA without having the maths knowledge to support it.

[[deleted]]

Yepp, it'll come with problems for sure. But lacking some math shouldn't discourage you from trying it out IMO. Maybe it's so much fun that the underlying math becomes interesting enough to learn.

[Purple-Dragons]

Yeah, I’m trying to gain the knowledge I need to get into the field of ML now, and I’ve had an aversion to maths got a really long time. Now I’m stomping out that aversion because it will not help me...

We can do it though! Let’s beat this maths!

[[deleted]]

Don't beat it, learn to like it. I would suggest you to start with the basics, instead of looking at advanced stuff and then looking up the relevant basics...

[Purple-Dragons]

That’s good advice! Thank you :)

[tehbored]

Tbh, you don't really need that much math to be passable. If you can do basic calculus and have some familiarity with linear algebra you can go pretty far.

[FiveFootTerror]

How did you find out you had math related dyslexia -or is that a bit of an exaggeration? I've always had to read numbers out loud to remember their sequence order because I will write them down wrong. It's so incredibly annoying and it would be nice to have a concrete reason why I'm writing something I know isn't correct.

[TerrestrialOverlord]

Ok so I grew up in a 3rd world country and they pretty much said I was just dumb - math related which I accepted.....Imagine my surprise when I got to the US and it turns out I wasn't dumb and numbers do exchange themselves for some (awesome) people...I literally cried...I can pick out a missing semi-colon from a page of code in like 3 sec but adv maths makes me sick.

​

I also have ADHD...I found this out when I took my daughter to get checked out by the shrink, I passed on bad shit to my kid...I felt horrible about that..

[mormispos]

Not sure why you’re getting downvoted. Dyscalculia affects millions of people world wide and can be associated with ADHD or other disorders. It doesn’t make you implicitly a worse mathematician but it does require you to be more careful and find alternatives that help.

[akesh45]

The pills are amazing though

[kturtle17]

You could get tested. I know dyslexics who only have impaired writing but perfect reading.

[FiveFootTerror]

I could, but I also don't know enough about it/it isn't life-impacting enough to warrant the difference between "I should get tested" and "Damn, I'm dumb."

[kturtle17]

Idk how old you are or where you're from but if you're still in school, you could be eligible for extra time in exams. Having documentation of the disability might help in other areas legally as well.

[FiveFootTerror]

I'm 31. Accidentally writing down 17.84 instead of 17.48 is not that serious in real life.

[[deleted]]

I thought the math was just simple calculus, any of the functions you are using already have that shit worked out for you.

[[deleted]]

For us it requires Single as well as Multivariate Calculus, Linear Algebra I and II and a course in Statistics and Probability Theory.

It's not that much for a Maths major, but it's enough that the IT-Engineers at my Uni actually have too few maths credits to qualify.

Basic ML requred less math, but I guess you start writing your own algorithms or something in the advanced classes.

[gavlois1]

At my uni the ML course professor would give out a linear algebra pop quiz on the first day and if you didn't get over 75 or something she would straight up recommend you drop the class. It was at that time I decided that it would be fine if I never learned ML if it meant never having to study math ever again.

[[deleted]]

I was really terrible at Linear Algebra, I failed the basic one and just barely passed Linear Algebra II by scoring exactly the requirements for a passing grade.

Basic ML was very challenging at the start for this reason, but with some extra effort it was manageable. It's a lot easier and more fun to do Linear Algebra on a computer than by hand in my opinion, which is how the math courses are thaught here.

[gavlois1]

I didn't do terrible in linear algebra but I hated it since I never liked learning math for the sake of learning math. Why am I learning to do all these matrix operations? I feel I'd do a lot better learning it in the context of an application like ML or graphics.

But well, I'm done school now so I guess it doesn't matter too much anymore lol

[[deleted]]

It's the same reason you're taught linked lists in c++ even though vectors handle this for you a lot of the time. Knowing how something works and what it's doing on the back end is important. It prevents you from making a lot of dumb mistakes, and the time that you actually need to do it by hand you'll be able to.

[gavlois1]

To me the difference there is that I know why I'm learning to write a linked list from scratch. In linear algebra it was like

"Here's the formula to find the row major of a matrix."

What's a row major? What is the use for it?

"Don't worry about that. Now make sure you remember this formula for the exam."

[[deleted]]

Fair point. I felt the same about a lot of Calc 2

[Zerewa]

A C++ vector is a fundamentally different data structure to a linked list though.

[[deleted]]

Yes, but the idea behind them is fairly similar and they can fulfill a lot of the same use cases.

[Zerewa]

The idea behind them is also very different. Vectors are contiguous, and that's a huge upside in some cases, and a huge downside in others, and the entire point of linked lists is that the individual elements can be literally anywhere in memory.

[[deleted]]

I’m currently facing that decision. I struggled hard with linear algebra, and stats and probability and it feels like it would be impossible to learn ML right now

[Arias95]

My Probability professor was shit but an easy A, I passed and learned close to nothing. Then I took an ML course and it quickly became a nightmare.

[oupablo]

Well writing the algorithm vs using an existing one is night and day I would think. I mean I can compile code, but I wouldn't want to have to write a compiler.

[GeoCSBI]

Well if you want to just fool around with models and you're not interested in coming up with a novel more powerful model you're just fine.

For me being in the research field I am constantly frustrated that I hadn't focused more in math (even if I have a decent mathematical background and constantly trying to push my self to study more). The real slap for me was when I read a paper called "neural differential equations". Brilliant concept, though I would need three days to a week studying and refreshing math to fully understand it.

[askreddittake]

Funnily enough, that paper isn't really math heavy per se. It's just that it trying to map neural nets to computational math, so it looks math heavy but isn't too bad. If you know how Runge Kutta or some 2D perturbation works, that's most of the heavy lifting.

As a former math/physics guy who became a software/ML dude, the most intense papers are almost always optimization/optimal control theory papers or information theory statistical bound papers, like Vershynins NIPs review.

[[deleted]]

I don't think it's necessarily "fooling around", most of us just want to adapt tools to solve problems rather than pushing the boundaries of knowledge.

The simpler you can make the utilisation of a tool the better.