# zergtant/pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

Repository: https://github.com/zergtant/pytorch-handbook
Canonical: https://ross.abutalabs.com/products/pytorch-handbook
Language: Jupyter Notebook
License Family: other
Topics: pytorch, pytorch-tutorials, pytorch-handbook, deep-learning, neural-network, machine-learning
Last push: 2024-07-25T07:17:26+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2830, "days_push": 769, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 21678, forks 5403 (observed 2026-08-28T04:11:31.969022+00:00)

## What it is
An open-source Chinese-language book (PyTorch Handbook) that helps beginners quickly get started with deep learning development and research using PyTorch. It consists of tested Jupyter notebook tutorials covering tensors, autograd, CNNs, RNNs, fine-tuning, visualization, and multi-GPU training.

## Use cases
- learn pytorch from scratch
- chinese pytorch tutorial book
- deep learning quick start with pytorch
- jupyter notebook examples for neural networks
- understand autograd and tensors
- multi-gpu distributed training tutorial
- mnist cnn classification example
- fine-tuning and transfer learning guide

## When to choose
- you prefer learning PyTorch in Chinese with runnable, tested notebooks
- you want a structured beginner-to-intermediate path from tensors to CNNs, RNNs, and multi-GPU training
- you need practical examples like MNIST classification, logistic regression, and fine-tuning

## When to avoid
- you need an official, always-current reference for the latest PyTorch release
- you require English-language materials
- you need a formal textbook with exercises and certification rather than community tutorials

## Facets
- artifact type: learning-resource
- maturity: active
- function: deep-learning, machine-learning, llm-training
- domain: deep-learning, machine-learning, tutorials, education
- platform: python, cross-platform
- tags: pytorch, chinese-language, jupyter-notebooks, open-book, neural-networks, tutorials, gpu

## Member repositories
- zergtant/pytorch-handbook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:31.969022+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 2026-08-29T16:57:50.061175+00:00, confidence not recorded.
  - readme: https://github.com/zergtant/pytorch-handbook (fetched 2026-08-28T04:11:31.969022+00:00, sha 7da3c391fc83)
- Data as of 2026-08-30T08:39:29.467469+00:00.