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visualize-ml/book3_elements-of-mathematics

7,461Jupyter NotebookAudience · generalComplexity · 1/5Setup · easy

TLDR

Interactive Jupyter Notebook companion to a Chinese-language textbook covering the mathematical foundations of machine learning, from basic arithmetic through linear algebra and matrix operations.

Mindmap

mindmap
  root((Elements of Math))
    Topics covered
      Basic arithmetic
      Linear algebra
      Matrix operations
      Data science basics
    Format
      Jupyter Notebooks
      Interactive code
      Math formulas
    Series context
      Feather Book series
      Chinese language
      Free companion
    Audience
      ML beginners
      Math learners
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Code map

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Things people build with this

USE CASE 1

Work through interactive math examples covering linear algebra and matrices to build foundations for machine learning.

USE CASE 2

Run and modify the provided Python code cells to see how mathematical concepts behave with real numbers.

USE CASE 3

Use the notebooks as a free study companion alongside the paid Feather Book series textbook.

Tech stack

PythonJupyter Notebook

Getting it running

Difficulty · easy Time to first run · 30min

Requires Python and Jupyter installed. README is in Chinese, notebooks include inline code that should run after a standard pip install.

In plain English

This repository contains the third book in a series called "Elements of Mathematics," which is part of a Chinese-language educational project nicknamed the Feather Book series. The book is described as covering a path from basic arithmetic all the way to machine learning, with topics including linear algebra, matrices, and data science concepts. The content is stored as Jupyter Notebooks, which are interactive documents that can combine written explanations, math formulas, and runnable code in the same file. This format is commonly used in data science and math education because it lets readers see both the theory and working examples side by side. The repository's README is written in Chinese and is quite brief. It provides links to discount purchase pages hosted on Zhihu, a Chinese knowledge-sharing platform, and notes that the open-source materials will remain available permanently. The authors also mention that readers who spot and report errors may receive a complimentary copy of the book as a thank-you. Based on the topics listed, the material covers mathematics subjects that are frequently used as foundations for machine learning, including linear algebra and matrix operations. The repository appears to be an open companion to a paid printed or digital book, with the Jupyter Notebooks serving as the interactive, freely accessible portion of the course.

Copy-paste prompts

Prompt 1
I am learning linear algebra for machine learning. Show me how to open and run the Jupyter Notebooks in this repo so I can follow along interactively.
Prompt 2
Using this repository's notebooks, walk me through how matrix multiplication works with a concrete Python example.
Prompt 3
Which notebooks in visualize-ml/book3 cover the math I need before starting a machine learning course?
Prompt 4
How do I set up a Python environment with Jupyter to run the notebooks in this repository on my laptop?
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