# MorvanZhou/PyTorch-Tutorial

Build your neural network easy and fast, 莫烦Python中文教学

Repository: https://github.com/MorvanZhou/PyTorch-Tutorial
Canonical: https://ross.abutalabs.com/products/morvanzhou-pytorch-tutorial
Homepage: https://mofanpy.com/tutorials/machine-learning/torch/
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: neural-network, python, pytorch-tutorial, batch-normalization, cnn, rnn, autoencoder, pytorch, regression, classification, batch, tutorial, dropout, dqn, reinforcement-learning, gan, generative-adversarial-network, machine-learning, pytorch-tutorials
Last push: 2023-03-23T05:01:42+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": 3407, "days_push": 1259, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 8465, forks 3090 (observed 2026-08-28T04:10:21.330865+00:00)

## What it is
A collection of PyTorch tutorial code examples and Jupyter notebooks by Mofan Zhou (莫烦Python), covering neural network basics through advanced architectures like CNN, RNN, AutoEncoder, DQN, and GAN. It accompanies free Chinese-language video and text tutorials on mofanpy.com.

## Use cases
- learn pytorch from scratch
- build my first neural network in pytorch
- understand cnn rnn gan with example code
- pytorch reinforcement learning dqn example
- learn batch normalization and dropout in pytorch
- chinese pytorch tutorial with videos
- example code for regression and classification in pytorch

## When to choose
- you are a beginner learning PyTorch, especially with Chinese-language instruction
- you want small, runnable example scripts for common neural network architectures
- you prefer learning via video/text tutorials paired with code

## When to avoid
- you need up-to-date code for the latest PyTorch APIs, as examples use older versions
- you need production-grade or well-engineered ML code
- you need comprehensive coverage of modern LLM or transformer techniques

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, reinforcement-learning
- domain: deep-learning, machine-learning, tutorials, reinforcement-learning
- platform: python, cross-platform
- tags: pytorch, neural-networks, tutorial, jupyter-notebook, chinese, cnn, rnn, gan, dqn, autoencoder

## Member repositories
- MorvanZhou/PyTorch-Tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:21.330865+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 2026-08-29T17:27:11.580028+00:00, confidence not recorded.
  - readme: https://github.com/MorvanZhou/PyTorch-Tutorial (fetched 2026-08-28T04:10:21.330865+00:00, sha aecde6f58507)
  - homepage: https://mofanpy.com/tutorials/machine-learning/torch/ (fetched 2026-08-29T08:27:08.084838+00:00, sha e19d6b1c7391)
  - site_page: https://mofanpy.com/about (fetched 2026-08-29T08:27:08.093802+00:00, sha 828465c2b53d)
  - site_page: https://mofanpy.com/tutorials/machine-learning/torch/install (fetched 2026-08-29T08:27:08.095769+00:00, sha bc58da73cd3f)
- Data as of 2026-08-30T08:39:29.467469+00:00.