From-scratch-machine-learning--From-mathematical-formulas-to-functioning-algorithms.

Repo description:

In this repository I will implement popular machine learning algorithms from their basic mathematical fundamentals to their code counterparts such as the implementations in scikit-Learn.

The purpose of this repository is:

1. To get a deeper feel and insight to the inner workings of these algorithms.
2. To gain a higher level of understanding, use cases , strengths and weaknesses of these many algorithms and their different implementations.

At the current moment I have done Linear Regression, Multiple Linear Regression, Logistic Regression and i'll be continuing to update this repo more as I start delving deeper into other algorithms..

I also implemented some binary classification metrics Binary Classification Metrics such as Precision, Recall, F1, & AUC in Python and explained them in a notebook.