Introduction
This repository, created by Minh-Chien Trinh at Jeonbuk National University, provides a comprehensive guide to building neural networks from scratch using Python. It serves as an educational resource tailored for graduate courses in Deep Learning and Deep Learning for Computer Vision. The project emphasizes practical implementation, allowing students to grasp the fundamental concepts of neural networks through hands-on coding.
Key Features:
- Educational Focus: Designed specifically for teaching purposes in graduate-level courses.
- Hands-On Learning: Encourages students to build neural networks from the ground up, enhancing their understanding of the underlying principles.
- Python Implementation: Utilizes Python, a widely-used programming language in data science and machine learning, making it accessible for students.
Use Cases:
- Graduate Courses: Ideal for instructors looking to provide practical coding experience in neural networks.
- Self-Learning: Suitable for individuals interested in deep learning who want to learn by doing.