Developed by A. M. Zayed Abdullah & Samira Bintey Haque
This repository contains all code, notebooks, and practical implementations developed during the AI Lab course at United International University. It includes hands-on examples of key Artificial Intelligence topics and serves as a reference for future learners and collaborators.
- 🔍 Search Algorithms – BFS, DFS, A*, etc.
- 🤖 Machine Learning – Supervised & unsupervised learning, classification, regression
- 🧠 Neural Networks – ANN & CNN with TensorFlow/Keras
- 🗣️ Natural Language Processing (NLP) – Text processing, classification
- 🎮 Reinforcement Learning – Basic RL principles and exercises
- 🧪 Mini Projects – Real-world problem-solving using AI
- 📝 Jupyter Notebooks – Tutorials, code walkthroughs, and experiments
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Language: Python
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Libraries & Frameworks:
- NumPy, Pandas, Matplotlib, Seaborn
- Scikit-learn
- TensorFlow / Keras
- NLTK / spaCy
- OpenAI Gym (for RL)
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Development Environment: Jupyter Notebook, Google Colab
Make sure you have Python 3.7+ and pip installed.
Clone the repository:
git clone https://github.com/yourusername/ai-lab-uiu.git
cd ai-lab-uiuInstall dependencies:
pip install -r requirements.txtOr open the notebooks directly in Google Colab.
Saifur Rahman
Faculty, Department of CSE
United International University
A. M. Zayed Abdullah
Student, Department of CSE
United International University 📧 a.m.zayedabdullah@gmail.com 🔗 LinkedIn Profile
Samira Bintey Haque
Student, Department of CSE
United International University 📧 s.b.h.tithi@gmail.com
Want to improve this project or add something new? Contributions are welcome!
- Fork this repository
- Create your branch (
git checkout -b feature/your-feature) - Commit your changes (
git commit -m 'Add feature') - Push to the branch (
git push origin feature/your-feature) - Open a pull request
This project is licensed under the GNU Public License 2.0. See the LICENSE file for details.
Let me know if you'd like a Markdown .md file version of this or help generating your requirements.txt!