Tutorial

Here are some related materials for your study, which will help you better understand the theory while also gaining practical knowledge.

Blockchain

• Basic knowledge: https://www.youtube.com/watch?v=UmVec9VHtpE&list=PLnTPdMjBRmAYehJkVbAXqxO-0cc9ALC6V

• Practice: https://github.com/tn606024/simplePBFT or https://www.blockemulator.com/

Federated / Machine Learning / Unlearning

• Deep Learning Practice: https://www.bilibili.com/video/BV1Y7411d7Ys

• Communication-efficient learning of deep networks from decentralized data: https://github.com/vaseline555/Federated-Learning-in-PyTorch

• FedEraser: Enabling Efficient Client-Level Data Removal from Federated Learning Models (Source Code: https://www.dropbox.com/scl/fi/p3q83ol0e751yfyv2cssh/FedEraser-Code.zip?rlkey=rhu67fyus0257j218306a6nib&dl=0)

• Machine Unlearning of Pre-trained Large Language Models (Source Code: https://github.com/yaojin17/Unlearning_LLM)

LLM and AI Agent

• NanoGPT: https://github.com/karpathy/nanoGPT

• MiniMind-LLM: https://github.com/jingyaogong/minimind

• Basic knowledge of AI Agent: https://www.youtube.com/watch?v=M2Yg1kwPpts

• Hello Agents: https://github.com/datawhalechina/hello-agents