Feature: Native Python Ridge Regression implementation to replace `glmnet`

Hello! I have been testing the Python version of the project and noticed that the biggest bottleneck right now is the reliance on the `glmnet` package (via `rpy2`).

I was wondering if it would be possible to achieve closely matching behavior using native packages like `scipy`/`numpy`. I quickly implemented a few modifications as a proof of concept and ran an early version.

Although the results of the best models still differ slightly from what is presented in the [tutorial1.ipynb](https://github.com/v4lentin3/Robyn/blob/main/python/src/robyn/tutorials/tutorial1.ipynb) notebook, the package manages to achieve very similar results in several aspects. I firmly believe that a full 100% native Python implementation is entirely possible.

I would like to open this discussion to know if the team is interested in moving towards a pure Python implementation for the Ridge regression without R dependencies, and if so, I'd be glad to help!