# MorvanZhou/tutorials

机器学习相关教程

Repository: https://github.com/MorvanZhou/tutorials
Canonical: https://ross.abutalabs.com/products/morvanzhou-tutorials
Homepage: https://morvanzhou.github.io/tutorials
Language: Python
License: MIT
License Family: permissive
Topics: machine-learning, neural-network, tensorflow, python, sklearn, theano, threading, multiprocessing, numpy
Last push: 2020-12-22T22:02:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3748, "days_push": 2080, "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 13010, forks 5669 (observed 2026-08-28T04:11:01.720828+00:00)

## What it is
Companion code repository for the MorvanPython (莫烦Python) tutorial series, covering machine learning, neural networks (TensorFlow, PyTorch, Keras, Theano), reinforcement learning, and Python fundamentals. It includes example code for data processing with NumPy, Pandas, and Matplotlib, plus threading, multiprocessing, and web scraping tutorials.

## Use cases
- learn machine learning with python from scratch
- tensorflow neural network tutorial examples
- reinforcement learning tutorial code
- learn numpy and pandas for data analysis
- python threading and multiprocessing examples
- beginner pytorch and keras examples
- web scraping tutorial in python

## When to choose
- you are a beginner wanting structured, video-backed tutorials on ML and Python basics
- you want runnable example code to follow along with MorvanPython lessons
- you want an accessible introduction to reinforcement learning or evolutionary algorithms

## When to avoid
- you need production-ready, maintained ML libraries rather than teaching examples
- you need up-to-date code for the latest TensorFlow or PyTorch versions, as the repo has not been updated since 2020
- you need advanced or research-grade implementations

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, reinforcement-learning, data-science, data-visualization, web-scraping, concurrency
- domain: machine-learning, deep-learning, data-science, tutorials, reinforcement-learning
- platform: python, cross-platform
- tags: tutorial-code, tensorflow, pytorch, numpy, pandas, sklearn, chinese-language, beginner-friendly

## Member repositories
- MorvanZhou/tutorials (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:01.720828+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 2026-08-29T17:13:35.792845+00:00, confidence not recorded.
  - readme: https://github.com/MorvanZhou/tutorials (fetched 2026-08-28T04:11:01.720828+00:00, sha feb0183a0da8)
  - homepage: https://morvanzhou.github.io/tutorials (fetched 2026-08-29T08:09:18.759991+00:00, sha c6b68d28b044)
- Data as of 2026-08-30T08:39:29.467469+00:00.