# MorvanZhou/Tensorflow-Tutorial

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Repository: https://github.com/MorvanZhou/Tensorflow-Tutorial
Canonical: https://ross.abutalabs.com/products/tensorflow-tutorial
Homepage: https://mofanpy.com/tutorials/machine-learning/tensorflow/
Language: Python
License: MIT
License Family: permissive
Topics: tensorflow, tensorflow-tutorials, gan, generative-adversarial-network, rnn, cnn, classification, regression, autoencoder, deep-q-network, dqn, machine-learning, tutorial, dropout, neural-network
Last push: 2020-10-31T02:48:09+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": 3402, "days_push": 2132, "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 4335, forks 1832 (observed 2026-08-28T04:08:46.055265+00:00)

## What it is
A collection of TensorFlow tutorial code from MorvanZhou (莫烦Python) covering neural network basics through advanced architectures like CNN, RNN, AutoEncoder, DQN, and GAN, with accompanying Chinese video and text lessons. It targets the legacy TensorFlow 1.x API from 2017 and has been superseded by the author's TensorFlow 2 and PyTorch tutorials.

## Use cases
- learn deep learning basics with tensorflow
- tutorial on building a cnn in tensorflow
- example code for gan and autoencoder
- learn rnn and lstm classification with tensorflow
- understand dqn reinforcement learning implementation
- chinese-language tensorflow course with videos
- learn dropout and batch normalization in neural networks

## When to choose
- you want beginner-friendly, example-driven deep learning tutorials with Chinese video lessons
- you need simple, self-contained scripts demonstrating CNN, RNN, GAN, or DQN concepts
- you are maintaining or studying legacy TensorFlow 1.x code

## When to avoid
- you are starting a new project with TensorFlow 2.x or PyTorch - use the author's updated tutorials instead
- you need current, maintained library code rather than educational examples
- you cannot read Chinese, since all explanations are in Chinese

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, deep-learning, llm-training
- domain: deep-learning, machine-learning, tutorials, education
- platform: python, cross-platform
- tags: tensorflow, neural-networks, cnn, rnn, gan, reinforcement-learning, dqn, autoencoder, chinese-language, tutorial-code

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

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:46.055265+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 2026-08-29T18:21:38.290743+00:00, confidence not recorded.
  - readme: https://github.com/MorvanZhou/Tensorflow-Tutorial (fetched 2026-08-28T04:08:46.055265+00:00, sha a647559af16d)
  - homepage: https://mofanpy.com/tutorials/machine-learning/tensorflow/ (fetched 2026-08-29T09:10:46.850461+00:00, sha 46153ba4acf1)
  - site_page: https://mofanpy.com/about (fetched 2026-08-29T09:10:46.859563+00:00, sha 828465c2b53d)
  - site_page: https://mofanpy.com/tutorials/machine-learning/tensorflow/install (fetched 2026-08-29T09:10:46.861531+00:00, sha ae58755c6eab)
- Data as of 2026-08-30T08:39:29.467469+00:00.