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What is hands-on-ml-zh?

apachecn/hands-on-ml-zh — explained in plain English

Analysis updated 2026-06-26

3,783CSSAudience · researcherComplexity · 1/5LicenseSetup · moderate

In one sentence

A Chinese translation of the popular machine learning book 'Hands-On ML with Scikit-Learn and TensorFlow', made by an open-source community, readable locally via GitBook, Docker, or a Python server.

Mindmap

mindmap
  root((hands-on-ml-zh))
    What it is
      Chinese book translation
      ML with Scikit-Learn
      ML with TensorFlow
    Audience
      Chinese learners
      ML beginners
    Delivery Methods
      GitBook
      Docker container
      Python local server
    Output Formats
      Website
      PDF
      EPUB
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Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Read the Hands-On Machine Learning book in Chinese by running a local website on your own computer.

USE CASE 2

Build an offline EPUB or PDF version of the translated book using GitBook for reading without internet.

USE CASE 3

Serve the book locally inside a Docker container to avoid installing Python dependencies.

What is it built with?

PythonGitBookDockerCSS

How does it compare?

apachecn/hands-on-ml-zhblivesta/animsitionsakofchit/system.css
Stars3,7833,7933,772
LanguageCSSCSSCSS
Setup difficultymoderateeasyeasy
Complexity1/51/52/5
Audienceresearcherdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires GitBook, Docker, or Python pip to serve the content, the hosted site is offline so local setup is the only way to read it.

Free to read and share for non-commercial purposes as long as you credit the authors and share any changes under the same license (Creative Commons BY-NC-SA).

So what is it?

This repository is a Chinese translation of the book "Hands-On Machine Learning with Scikit-Learn and TensorFlow," second edition, produced by the ApacheCN open-source community. The original book is a widely used guide to machine learning in Python, covering tools like Scikit-Learn for classical machine learning and TensorFlow for deep learning. The translation was published as a website and as a readable online document. However, the repository description notes that the site has been taken offline due to copyright concerns. The project was distributed under a Creative Commons Attribution-NonCommercial-ShareAlike license. For those who want to build or run the content locally, the README (written in Chinese) provides instructions for three delivery methods. You can build it with gitbook, a tool that converts structured text files into a readable website or ebook formats including PDF, EPUB, and MOBI. Alternatively, you can run a local web server using either a Docker container or a Python package installable via pip, both of which serve the content at a local port in your browser. The README is short and written in Chinese, mostly focused on setup commands rather than describing the content of the book itself. The repository represents a community-driven localization effort aimed at making widely used English technical books accessible to Chinese-speaking learners, which is a common practice in the ApacheCN community across many programming topics. Because the hosted site is offline and the project raises copyright questions about the translated material, its current practical use is limited. Related resources from the same ApacheCN group, including a Chinese translation of another Python data analysis book, are also linked.

Copy-paste prompts

Prompt 1
Show me how to clone the apachecn/hands-on-ml-zh repo and serve it locally as a website using Python so I can read it in my browser.
Prompt 2
Walk me through building a PDF from the apachecn/hands-on-ml-zh GitBook content on a Windows machine.
Prompt 3
Set up a Docker container to serve the apachecn/hands-on-ml-zh book locally and tell me which port to open in my browser.

Frequently asked questions

What is hands-on-ml-zh?

A Chinese translation of the popular machine learning book 'Hands-On ML with Scikit-Learn and TensorFlow', made by an open-source community, readable locally via GitBook, Docker, or a Python server.

What language is hands-on-ml-zh written in?

Mainly CSS. The stack also includes Python, GitBook, Docker.

What license does hands-on-ml-zh use?

Free to read and share for non-commercial purposes as long as you credit the authors and share any changes under the same license (Creative Commons BY-NC-SA).

How hard is hands-on-ml-zh to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is hands-on-ml-zh for?

Mainly researcher.

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