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datawhalechina/leedl-tutorial

Analysis updated 2026-06-24

★ 16,553Jupyter NotebookAudience · researcherComplexity · 2/5Setup · easy

TLDR

Chinese deep learning tutorial book derived from Li Hongyi's lecture course, distributed as a downloadable PDF covering CNNs, GANs, diffusion, BERT, and ChatGPT.

Mindmap

mindmap
  root((leedl-tutorial))
    Inputs
      Li Hongyi lectures
      Notebook examples
    Outputs
      Downloadable PDF book
      Chapter explanations
    Use Cases
      Study deep learning in Chinese
      Self-paced course companion
      Reference for modern AI topics
    Tech Stack
      Jupyter Notebook
      Python
      Deep Learning
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Code map

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What do people build with it?

USE CASE 1

Download the PDF and use it as a Chinese language textbook companion to Li Hongyi's deep learning course.

USE CASE 2

Read selected chapters to get a structured intro to CNNs, GANs, diffusion models, and BERT.

USE CASE 3

Use the included notebooks to run example code while studying each topic.

USE CASE 4

Share the book with students who want a free Chinese deep learning reference.

What is it built with?

Jupyter NotebookPythonDeep Learning

How does it compare?

datawhalechina/leedl-tutorialinfrasys-ai/aisysteminstillai/tensorflow-course
Stars16,55316,74416,290
LanguageJupyter NotebookJupyter NotebookJupyter Notebook
Setup difficultyeasyeasyeasy
Complexity2/52/51/5
Audienceresearcherresearcherdata

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

The deliverable is a PDF downloaded from the GitHub releases page, no install needed unless you want to run the notebooks.

In plain English

Based on the description and topics, this appears to be a deep learning tutorial resource based on a course by educator Li Hongyi (also known as Lee Hung-yi). The description is in Chinese and indicates it is a PDF-downloadable tutorial that the instructor has personally recommended. The topics cover core deep learning concepts including convolutional neural networks (CNNs, a type of AI used for image recognition), generative adversarial networks (GANs, a technique for generating synthetic data), diffusion models (used in AI image generation), BERT (a natural language processing model), ChatGPT-related content, and general machine learning. The README does not provide further detail about the specific content structure, prerequisites, or how to use the material beyond that it is available as a downloadable PDF via the GitHub releases page.

Copy-paste prompts

Prompt 1
Summarize the chapter structure of the leedl-tutorial PDF and tell me which chapters cover diffusion models.
Prompt 2
Translate the GAN chapter of leedl-tutorial from Chinese to English so I can study it.
Prompt 3
Help me set up a Jupyter environment to run the example notebooks from leedl-tutorial.
Prompt 4
Use the leedl-tutorial CNN chapter to walk me through building a small image classifier in PyTorch.
Prompt 5
Compare what leedl-tutorial covers about BERT versus the original BERT paper.

Frequently asked questions

What is leedl-tutorial?

Chinese deep learning tutorial book derived from Li Hongyi's lecture course, distributed as a downloadable PDF covering CNNs, GANs, diffusion, BERT, and ChatGPT.

What language is leedl-tutorial written in?

Mainly Jupyter Notebook. The stack also includes Jupyter Notebook, Python, Deep Learning.

How hard is leedl-tutorial to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is leedl-tutorial for?

Mainly researcher.

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