This is a Machine Learning library designed to provide implementations of key algorithms, including:
-Linear Regression
-Polynomial Regression
-Linear Classifier
-Decision Trees
-Support Vector Machine (SVM)
-Neural Network

This project was developed as part of a Machine Learning course under the supervision of Prof. Hedi Tebia.

Features
-Simple and intuitive API for building and training models
-Implementation of core machine learning algorithms
-Customizable hyperparameters for advanced users

Installation
Provide installation instructions if applicable (e.g., via pip or directly from the repository)