This repository is a reflection of my journey in learning deep learning, specifically focusing on the implementation of neural networks. It serves as a practical exploration of various deep learning concepts and techniques, with a particular emphasis on diffusion models and their components.
Through this project, I aim to deepen my understanding of how to construct and optimize neural networks, leveraging architectures like U-Net and mechanisms such as self-attention. The repository not only documents my progress but also provides a comprehensive guide for others interested in similar topics.
Feel free to explore the code, experiment with the models, and contribute to the ongoing learning process.