Welcome to my Machine Learning Course Repository!
This project contains the code and resources for my machine learning course at Tarbiat Modares University. Throughout the course, we explore a wide range of topics, including:
- Supervised Learning: Techniques for predicting outcomes based on labeled training data.
- Unsupervised Learning: Approaches for analyzing data without labeled responses.
- Deep Learning: Advanced methods for modeling complex patterns using neural networks.
The code in this repository is designed to assist students in understanding the fundamental concepts and techniques related to machine learning. Each script includes practical examples and tutorials to facilitate hands-on learning and application to real-world problems.
The project is implemented in Python and utilizes the following libraries:
- NumPy: For numerical computations.
- Pandas: For data manipulation and analysis.
- Matplotlib: For data visualization.
- Scikit-learn: For standard machine learning algorithms.
- PyTorch: For deep learning applications.
This repository is primarily aimed at students who are new to machine learning. The code is well-documented, providing explanations and comments to ensure clarity for beginners.
I created this project to share my knowledge and experiences with those interested in learning about machine learning. I hope you find the resources helpful!
If you have any questions, suggestions, or feedback, please feel free to reach out to me:
Special thanks to the faculty and peers at Tarbiat Modares University for their support and inspiration in developing this course.
Happy Learning! 🚀