AI-ML Repository

Welcome to the AI-ML repository! This repository contains various AI and Machine Learning projects implementing different algorithms and techniques learned from my courses. Each project is structured to demonstrate key concepts, methodologies, and applications in AI and ML.

Table of Contents

• Overview
• Projects
• Technologies Used
• Installation
• Usage
• Contributing
• License
• Contact

Overview

This repository serves as a collection of AI and ML projects, covering a range of supervised, unsupervised, and reinforcement learning algorithms. The projects are designed to provide practical implementations of theoretical concepts learned in various AI/ML courses.

Projects

Below is a list of implemented projects and algorithms:

1. Reinforcement Learning
   • Q-Learning
   • Deep Q-Networks (DQN)

Technologies Used

• Python
• TensorFlow / PyTorch
• Scikit-learn
• NumPy / Pandas
• Matplotlib / Seaborn
• OpenCV (for image processing tasks)

Installation

To run the projects locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/leneyxis/AI-ML.git
   cd AI-ML

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

Usage

Each project contains a Jupyter Notebook (.ipynb) with explanations and code implementations. Navigate to a specific project and run the corresponding notebook/script.

To start Jupyter Notebook:

jupyter notebook

Contributing

Contributions are welcome! If you have any improvements, bug fixes, or new projects to add, feel free to fork this repository and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any queries or suggestions, feel free to reach out:

• Email: syedumerahmed97@gmail.com
• GitHub: Leneyxis

Happy coding! 🚀