This repository is a collection of my coding projects from the "Foundations of Artificial Intelligence" course. Here, you will find a series of projects implemented from scratch in Python, covering a wide range of fundamental AI concepts and algorithms.
The purpose of these projects is to delve into the building blocks of Artificial Intelligence. Each project focuses on implementing and understanding a fundamental AI concept or algorithm. These projects were part of my journey in the "Foundations of Artificial Intelligence" course and I'm excited to share them here.
Here are some of the main projects you'll find in this repository:
- A Search Algorithm*: A pathfinding algorithm widely used in AI.
- Simulated Annealing: A probabilistic technique for approximating the global optimum of a given function.
- Genetic Search Algorithm: An optimization or search technique inspired by the process of natural selection.
- ID3 Decision Tree: A machine learning algorithm for decision making, implemented from scratch.
To get started with these projects:
- Clone the repo
git clone https://github.com/[your_username]/[repo_name].git
Navigate to the project of your choice and follow the instructions in the respective README files. Contributing Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
Fork the Project Create your Feature Branch (git checkout -b feature/AmazingFeature) Commit your Changes (git commit -m 'Add some AmazingFeature') Push to the Branch (git push origin feature/AmazingFeature) Open a Pull Request Contact Adir Serruya - [email protected]
Project Link: https://github.com/[your_username]/[repo_name]