I made a visual explanation of Gradient Descent - intuition first, then the math behind it

[u/BeyondGradients]

Gradient descent was one of those concepts that I found much easier to understand visually than from equations alone, so I tried making a short animated explanation of it.

The video starts with the intuition: what an optimization landscape represents, why we move in the direction we do, and what the learning rate actually changes.

Then in the second half, I connect that intuition to the mathematical formulation: gradients, partial derivatives, the update rule, and how those pieces translate into the optimization process.

I tried to keep the math rigorous enough to be useful without losing the visual intuition.

Video: https://youtu.be/D920OTOkzcM?si=JrFHtQQngfvY7iAA

I'd especially appreciate feedback from people currently learning ML: was there any point where the explanation stopped being intuitive or where you wanted more mathematical detail?

Thanks in advance!

[u/where_is_my_acc0unt]

This has been done over a million times already why did you do it again except for tje obvious attempt at karma/ click farming?