Introduction to Modern Statistics is an open college-level textbook covering multivariable relationships and simulation-based inference.
Information Theory, Inference, and Learning Algorithms by David J.C. MacKay
Information Theory, Inference, and Learning Algorithms is a textbook with related resources by David MacKay.

About Information Theory, Inference, and Learning Algorithms by David J.C. MacKay
This is the homepage for Information Theory, Inference, and Learning Algorithms, a textbook by David J.C. MacKay published by Cambridge University Press in 2003 (ISBN-13 9780521642989). The site presents the book along with related materials, including a corrections page, a software section, an extras section, and a question page.
The homepage describes the book as covering topics from Shannon's fundamental theorems to the theory of LDPC codes, based on a quoted review. The site also offers teachers all the book's figures for download and provides a single-document view of the site. It lists a 2012 set of 16 video lectures by MacKay and a 2009 book on sustainable energy by the same author.
Key features
- Textbook on information theory, inference, and learning algorithms
- Corrections page listing errata for the book
- All book figures available for download for teachers
- Set of 16 video lectures by David MacKay
- Software section linked from the homepage
- Option to view the site as a single document
- Provides figures for download for teachers
- Includes video lectures by the author alongside the text
- Lists corrections to the book on a dedicated page
Information Theory, Inference, and Learning Algorithms by David J.C. MacKay at a glance
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Good for
- Educators
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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