# mml-book.github.io

**Repository Path**: airbmw/mml-book.github.io

## Basic Information

- **Project Name**: mml-book.github.io
- **Description**: Mirrors from https://github.com/mml-book/mml-book.github.io.git
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: https://github.com/mml-book/mml-book.github.io.git
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-01-28
- **Last Updated**: 2026-01-30

## Categories & Tags

**Categories**: Uncategorized

**Tags**: mathematics, Machine-learning, 机器学习, 数学, AIM

## README

# mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"

[https://mml-book.com](https://mml-book.com)

Copyright 2020 by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong. To be published by Cambridge University Press.

We are in the process of writing a book on Mathematics for Machine Learning that motivates people to learn mathematical concepts. The book is not intended to cover advanced machine learning techniques because there are already plenty of books doing this. Instead, we aim to provide the necessary mathematical skills to read those other books.

We split the book into two parts:

* Mathematical foundations
* Example machine learning algorithms that use the mathematical foundations

We aim to keep this book reasonably short, so we cannot cover everything. We will also provide exercises for part 1 and jupyter notebooks for part 2 of the book.

The notebooks can be run live on [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mml-book/mml-book.github.io/master?filepath=tutorials).

Alternatively try them directly on **Google Colab** 

| Title | Tutorial Notebook  | Solution |
|-|:-:|:-:|
| Linear Regression  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_linear_regression.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_linear_regression.solution.ipynb) |
|  Principal Component Analysis (PCA) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_pca.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_pca.solution.ipynb) |
| Gaussian Mixture Model (GMM) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_gmm.ipynb) | [ ![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_gmm.solution.ipynb)|