I Wanted To Build AI. Instead I Met Linear Algebra

VishnuRv — Sun, 24 May 2026 17:21:42 +0000

When I first started learning machine learning, I was genuinely confident.

In my head ML was basically:

understand pipelines
know which model to use
clean some data
train the model
Google syntax when needed
boom… AI engineer arc begins ☠️🙏

But today I got hit by reality.

I started learning systems of linear equations, matrices, and how to represent equations as matrices.

At first I was like:
*Cool engineering math again

Then suddenly it clicked.

THIS is what machine learning is actually built on.

Not the tutorial side.
Not the “train model in 5 lines” side.

The actual core.

I realized if I ever want to:

understand why a model failed
debug training issues
read research papers
work on serious ML projects
survive in a research lab

then I can’t just avoid math forever and keep pretending the libraries are doing magic behind the scenes 😭🙏

Today was the first time I actually understood that terms like:

weights
features
transformations
optimization

are not just random fancy ML words.

There’s real mathematics underneath them.

And honestly?
That realization shocked me more than the equations themselves.

So now I’m starting something different:
learning math side by side while building models.

Not because I suddenly became a math lover ☠️🙏

But because I finally understood WHY it matters.

I don’t want to walk into an AI lab one day calling myself an ML engineer while secretly not understanding what the model is even doing internally.

So yeah
today matrices humbled me.

And this is probably just the beginning 😭🙏

If you’ve gone through this phase already, drop your survival tips ☠️🙏

Escaping the tutorial trap and starting my ML training arc

VishnuRv — Sat, 09 May 2026 10:19:40 +0000

You ever start watching an anime or a series on episode 12 and just sit there wondering wtf is going on? 😂

Yeah, that’s exactly what it would feel like if I just dropped my Kaggle code today without an intro. So, let’s start at Episode 1.

Hey, I'm Vishnu. I’m currently a 1st-year B.Tech CSE student, but I'm playing the long game. My ultimate endgame is pursuing my Master’s in AI and Machine Learning at a top research lab in Japan.

Recently, I had this massive realization: the clean, custom datasets they give you in basic ML tutorials are basically a trap. They teach you the syntax, but they don't teach you how to survive. The real world is a messy warzone of missing values, typos, and useless noise.

I realized I need to treat Data Science less like a calculator and more like detective work.

I’ll be using Dev.to as my captain’s log. I'll be posting my Kaggle wins (actually just hit a 78% accuracy on my first real Medical Insurance dataset today!), the bugs that fry my brain, and probably a lot of anime analogies to explain complex ML math (obviously I use this to teach myself lol)

If you are also on the tech grind or just want to watch a disciplined newbie, try to decode the AI world from scratch and make it to Japan, stick around.

The real work starts now. Let's get it. 💻🔥⚡

if you ever want to connect with me and share some thoughts absolutely, do and connect with me 😉

DEV Community: VishnuRv

I Wanted To Build AI. Instead I Met Linear Algebra

Escaping the tutorial trap and starting my ML training arc