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TingsongYu/PyTorch-Tutorial-2nd resource

《Pytorch实用教程》(第二版)无论是零基础入门,还是CV、NLP、LLM项目应用,或是进阶工程化部署落地,在这里都有。相信在本书的帮助下,读者将能够轻松掌握 PyTorch 的使用,成为一名优秀的深度学习工程师。 observed · 2026-08-28

github.com/TingsongYu/PyTorch-Tutorial-2nd · homepage · Jupyter Notebook observed · 2026-08-28

Health v2 · maintenance only

67/100

  • Activity 99
  • Release rhythm 8
  • Longevity 100

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1721
  • days_rel: n/a
  • days_push: 11
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

4584 stars · 491 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A free open-source Chinese-language book and companion Jupyter Notebook codebase teaching PyTorch from basics through CV, NLP, and LLM applications to inference deployment with ONNX and TensorRT. It is structured in three parts: PyTorch fundamentals, industry application projects, and production deployment including PTQ/QAT quantization.

Use cases

  • learn pytorch from scratch
  • pytorch tutorial for beginners
  • learn deep learning with practical projects
  • object detection with yolov5 tutorial
  • deploy pytorch models with onnx and tensorrt
  • fine-tune and run open-source llms like qwen
  • learn model quantization ptq and qat
  • study transformer bert and gpt models

When to choose

  • you want a structured, project-driven path from PyTorch basics to deployment
  • you prefer Chinese-language learning materials with runnable Jupyter Notebook code
  • you need coverage of CV, NLP, and LLM tasks in one resource
  • you want to learn inference optimization with ONNX, TensorRT, and quantization

When to avoid

  • you need an English-language textbook
  • you want a maintained software library rather than educational material
  • you need a formal certification or instructor-led course
  • you already need only advanced research-level material beyond engineering practice

Facets

learning-resource · maturity active

machine-learning deep-learning computer-vision nlp llm-inference data-visualization developer-tools deep-learning machine-learning computer-vision large-language-models tutorials education python cross-platform pytorch tutorial jupyter-notebook onnx tensorrt model-quantization yolov5 qwen transformer model-deployment chinese-language natural-language-processing gpu

2 sources

Member repositories

RepositoryRoleHealth v2
TingsongYu/PyTorch-Tutorial-2ndmain67

For agents

markdown · JSON · MCP: product_card(name="TingsongYu/PyTorch-Tutorial-2nd")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem