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One Reason You May Struggle To Learn ML/AI

Tech With Tim 45 views

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Well looks like im screwed
Comment from : @kylehewson6258

Linear algebra and multivarient gradient descent : advanced math topicssorry bro, I was rolling on the ground laughing 😂😂😂
Comment from : @andrewhabroad

Honestly bro,brIf u passed, 12th grade maths,brIt's only at max 2-3 months of maths,brI'm saying 3 months , side by side, u can practice coding and u can make projects ❤
Comment from : @NasimaBegum-dg3ht

@techwithtim is AI ML hard for a beginner to understand or study
Comment from : @Chaoticwhale4446

linear algebra and gradient descent are high school level arent they? /gen, ofc most ppl wont have it in the back of their minds but a quick refresh course will remind you of the basics, calculus and algebra needed for ml is actually pretty simple
Comment from : @ght0076

Gradient descent involves very simple math
Comment from : @Djellowman

Nah with AI in its current stay it's not hard
Comment from : @ThisIsDan-i

learning ai yeah lmao
Comment from : @raccoon2276

Could u make Algo videos or python all DS
Comment from : @adityanayak20

Good info
Comment from : @tictoc1433

I wish someone had told me long ago, that being a passable software engineer didn't require expert math, I would've been more open to learning the science long ago
Comment from : @travis8229

One reason that struggling my ML journey is because my device didn't strong enough to run it 😅
Comment from : @ban_droid

Not really, the maths in ML are quite limited and simple, and most of it are 100 taken care by simple blackbox functions and tensor specialized HW The understanding, analytical side and innovative part is the hardest part in ML, the math part is trivial even compared to high school maths, and mostly skippable
Comment from : @Songfugel

Of course brother every activities need focus and time
Comment from : @shapiekhan

As a Data Scientist I can confirm that it can be very frustrating Unlike with software engineering, with ML you never know what you're gonna get Maybe you spend a ton of time coding, cleaning data, and engineering features only to find out that your data simply doesn't allow you to build a sufficiently accurate model In contrast, in software engineering, you'll always have something to show if you put in enough work
Comment from : @datamonster3212