# TingsongYu/PyTorch-Tutorial-2nd

《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。

Repository: https://github.com/TingsongYu/PyTorch-Tutorial-2nd
Canonical: https://ross.abutalabs.com/products/pytorch-tutorial-2nd
Homepage: https://tingsongyu.github.io/PyTorch-Tutorial-2nd/
Language: Jupyter Notebook
License Family: other
Topics: computer-vision, deepsort, diffusion-models, onnx, pytorch, pytorch-tutorial, tensorrt, yolov5, llm, qwen
Last push: 2026-08-22T03:35:48+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 1721, "days_push": 11, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4584, forks 491 (observed 2026-08-28T04:08:54.594566+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, computer-vision, nlp, llm-inference, data-visualization, developer-tools
- domain: deep-learning, machine-learning, computer-vision, large-language-models, tutorials, education
- platform: python, cross-platform
- tags: pytorch, tutorial, jupyter-notebook, onnx, tensorrt, model-quantization, yolov5, qwen, transformer, model-deployment, chinese-language, natural-language-processing, gpu

## Member repositories
- TingsongYu/PyTorch-Tutorial-2nd (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:54.594566+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:19:52.714709+00:00, confidence not recorded.
  - readme: https://github.com/TingsongYu/PyTorch-Tutorial-2nd (fetched 2026-08-28T04:08:54.594566+00:00, sha 7eb4faa50e0c)
  - homepage: https://tingsongyu.github.io/PyTorch-Tutorial-2nd/ (fetched 2026-08-29T09:05:18.236574+00:00, sha 385b5aff35bf)
- Data as of 2026-08-30T08:39:29.467469+00:00.