Machine Learning Demos Repository

Welcome to my Machine Learning Demos Repository! 🚀

This repository contains implementations and demonstrations of fundamental machine learning concepts using Python and NumPy. Each sub-repository focuses on a specific topic, and the code is accompanied by detailed explanations and applications on demo data.

Repositories Overview:

1. Linear Regression

   • Repository Link
   • This repository covers the basics of linear regression, showcasing a simple implementation and application on demo data.

2. Linear Regression (Normal Equations)

   • Repository Link
   • Explore an alternative approach to linear regression using normal equations, with practical examples and explanations.

3. Multiple Regression

   • Repository Link
   • Learn how to extend linear regression to handle multiple input features.

4. Polynomial Regression

   • Repository Link
   • Dive into polynomial regression, a powerful technique for capturing non-linear relationships in data.

How to Use:

1. Clone the Repository:

   • Clone this main repository to your local machine using the following command:

     git clone git@github.com:oubrikyoussef/Machine-Learning.git

2. Navigate to a Sub-Repository:

   • Navigate to the specific sub-repository of interest using the cd command:

     cd  Machine-Learning/linear-regression

3. Explore and Run Demos:

   • Open the Jupyter Notebook provided in each sub-repository to explore the code and run the demo applications.

4. Connect with Me:

   • If you have any questions, suggestions, or just want to connect, feel free to reach out on LinkedIn!

Feel free to explore, learn, and contribute! If you have any questions or suggestions, don't hesitate to reach out.

Happy coding and learning! 🌟