I had some fun tonight writing a linear regression...

# datascience

[thomasnield]

I had some fun tonight writing a linear regression algorithm from scratch in Kotlin. To execute gradient descent, I spent an hour figuring out partial derivatives, which basically is a Calculus derivative targeting one variable at a time, assuming all the other variables are constant.

The partial derivatives can then be used to measure slope of the error, and when that slope approaches 0 you hit a local minimum and found an optimal line. I'll post a video on this later.

[Source Code is on GitHub](https://gist.github.com/thomasnield/fbe2e2205233388577e6abe6f5bbe897)

[Desmos Graph](https://www.desmos.com/calculator/ntomwigo6k)