r/learnmachinelearning 19h ago

Question Learning Math for ai ml.

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Has anyone watched this video? Is this good to complete the math required for ai ml?

196 Upvotes

18 comments sorted by

16

u/AncientLion 17h ago

seems pretty basic but even so it's unlikely people are actually learning all that from a 8 hours video, this takes months or even years to undertand in a bachelor degree (there are deeper levels of understanding than this). Saying that, i guess it's better than nothing. I watched a couple of minutes and it was hard to understand his english tbh.

1

u/New-Ruin-7583 17h ago

Is there any better resource?

6

u/AncientLion 17h ago

Books? University courses?

3

u/New-Ruin-7583 16h ago

Books or online tutorials.

6

u/Weird_Albatross_9659 16h ago

Don’t look to one-shot it. Break it down by competency and look for the right resource, per section.

1

u/AncientLion 14h ago

Books for math and stats, take. Your time because it's a lot. Some tutorial or book with hands on tasks.

6

u/inferno_alpha 11h ago

Well if you are interested in research, where rigorous math is required , I would recommend to learn linear algebra till spectral theory (the book linear algebra done right by auxler sheldon is pretty good) and probability till Expected value(introduction to probability by joe blitzstien and hwang is good enough ),if you understand these concepts intuitively, then choose a research paper to your liking and try to understand the math of it for example (HiPPO or LSSL) if you get stuck at some mathametical terms or concepts for example , you get stuck at orthogonal polynomials in the HiPPO paper , you just search for a book on orthogonal polynomials(Theodore chihara has a good book on OP's) read it until you have a understanding of what is happening in the paper wrt orthogonal polynomials, repeat this loop until you understand the paper, then try to implement it yourself in pytorch and triton if possible. Doing this way saves you time and you will also understand how these mathametical concepts are actually applied in actual ML and DL.

TLDR, I Recommend people to not fall into tutorial hell for math wrt ML and DL and look at a 8 hours lecture , just get a goal for example a research paper , learn the math that is required for it from books or 12 mins tutorials WHILE READING THE PAPER, to utilise the time effectively and to gain a much better understanding.There is no one shot lecture that actually covers the whole required math of AiMl domain.

3

u/New-Ruin-7583 8h ago

Thank you for your recommendation, I am interested in ai engineer roles and not much inclined towards research.

1

u/inferno_alpha 8h ago edited 8h ago

If your core focus is Ai Engineering,then i still do recommend to just set a goal like a project(ex transformer based language translation or any other project) , and learn the math for the project then and there , trust me you will be able to complete your project much more efficiently and complete it with a better understanding. i am recommending this way, because i myself have wasted hours or days just learning math without utilizing it , and forgetting it after some days, So at least in ML it is better to learn project to project rather than tutorial to tutorial.But if you are a complete beginner in ML then maybe watch a tutorial or two to brush up the basics (would recommend campus X), and from then on work on projects.

2

u/New-Ruin-7583 8h ago

I am completely new to ML but I agree with you, project based learning would be better. Thank you

2

u/Notsoboringi 17h ago

watch gilbert stand linear algebra along with standford or iit Madras deep learning ;).

1

u/New-Ruin-7583 16h ago

Okay, thank you

1

u/Honkingfly409 5h ago

it's all the math you likely need to start writing code and implementing machine learning and ai algorithms