ML_practice | Practice using the sklearn library

[Much better question, btw]

It's hard to know exactly what's going on here, but basically your cost is going the wrong direction and spiraling out of control, which results in an overflow when you try to square the value.

I think in your case it boils down to your step size (alpha) being too big which can cause gradient descent to go the wrong way. You need to watch the cost in gradient descent and makes sure it's always going down, if it's not either something is broken or alpha is to large.

Personally, I would reevaluate the code and try to get rid of the loops. It's a matter of preference, but I find it easier to work with X and Y as column vectors. Here is a minimal example: