This repository contains my personal lab implementations and projects for the course "Foundations of Deep Learning", taught by the esteemed Professor Sun Xiaoguang at Fudan University during the Spring semester of 2025.
This repository serves as a comprehensive record of my learning journey into Deep Learning. It includes all the hands-on work that brought the theoretical concepts to life, from basic neural networks to advanced architectures like Transformers.
To explore the homework assignments, including detailed lab reports and source code (in Jupyter Notebook or Python format), please switch to the respective branches.
The coursework covered a wide range of fundamental and cutting-edge topics, with practical implementations including but not limited to:
- Convolutional Neural Networks (CNNs) for image classification and style transfer.
- Recurrent Neural Networks (RNNs) & LSTMs for sequential data analysis.
- Transformer Models and their application in Natural Language Processing (NLP).
- Diffusion Models for image generation and reconstruction.
- Large Multimodal Models for analysis of multimodal data.
- Local deployment and interaction with Large Language Models (LLMs) using tools like Ollama.
- Deep reinforcement learning is used to design games according to huggingface
This course was a pivotal point in my academic path. As a Pharmacy student with no prior computer science background, I was initially hesitant. However, Professor Sun's exceptional ability to demystify complex concepts and his focus on teaching us "how to learn" made all the difference.
The hands-on experience gained here—from building RNNs from scratch to deploying LLMs locally—not only unveiled the immense potential of AI but also gave me the confidence to fully transition into AI-driven research. I am profoundly grateful to Professor Sun for being the guide who opened this door to an interdisciplinary and exciting future.
"A teacher affects eternity; he can never tell where his influence stops."
— This repository is a small testament to that influence.
I have also uploaded the course presentation slides (PPTs/) used by Professor Sun, which are models of clarity and succinctness and were instrumental in my understanding.
Last updated: Novemeber 2025* for structured data.
- Local deployment and interaction with Large Language Models (LLMs) using tools like Ollama.
