This Machine Learning library offers implementations of essential algorithms, including:

-Linear Regression
-Polynomial Regression
-Linear Classifier
-Decision Trees
-Support Vector Machine (SVM)
-Neural Networks

This project was created as part of a Machine Learning course, supervised by Prof. Hedi Tebia.

Features:
-Easy-to-use API for building and training models
-Comprehensive implementations of core machine learning algorithms
-Support for customizable hyperparameters, catering to both beginners and advanced users
Installation

Provide instructions for installation, such as using pip or cloning the repository, if applicable.