Mml-Book.Github.Io

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mml-book.github.io is a companion webpage for the book "Mathematics For Machine Learning." It offers resources like exercises and Jupyter notebooks to support learning mathematical concepts for machine learning.

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Pricing

Free

Free tier

Yes

API

Skill level

Technical

About

What is mml-book.github.io?

mml-book.github.io serves as the official companion webpage for the book "Mathematics For Machine Learning" by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong. This resource is designed to motivate and equip individuals with the necessary mathematical skills to understand advanced machine learning techniques. The site provides supplementary materials, including exercises for the mathematical foundations section and Jupyter notebooks for the example machine learning algorithms. These notebooks can be run live on Google Colab, offering an interactive learning experience. The book aims to be concise, focusing on core mathematical concepts rather than exhaustive coverage of advanced ML techniques, making this companion site a valuable educational aid.

Best used for

Ideal for professors and teachers who need to provide supplementary materials for mathematics courses related to machine learning, offer interactive coding examples, and support student self-study. Especially valuable for those using the "Mathematics For Machine Learning" textbook.

Common actions

learn mathematics

teach machine learning

access educational resources

run code examples

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Capabilities

Key features

Companion webpage
Mathematical exercises
Jupyter notebooks
Google Colab integration
Machine learning examples

Target Audience

professorteacher

Integrations

google-colab

Pricing & Plans

Free

FAQs

What kind of content is available on mml-book.github.io?

The website provides a range of supplementary materials for the "Mathematics For Machine Learning" book. This includes exercises to reinforce mathematical foundations and Jupyter notebooks that demonstrate example machine learning algorithms, offering practical application of the concepts.

Are the Jupyter notebooks interactive?

Yes, the Jupyter notebooks provided on the companion webpage are designed for interactive learning. They can be run directly on Google Colab, allowing users to execute code, experiment with parameters, and see immediate results without needing a local setup.

Is this website suitable for beginners in machine learning?

While the book and website focus on mathematical foundations, they are intended to provide the necessary skills to understand machine learning. It's suitable for those looking to build a strong mathematical background for ML, rather than covering advanced ML techniques directly.

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