Why Machines Learn: The Elegant Maths Behind Modern AI
Elegant Maths: Why Machines Learn by Anil Ananthaswamy explains the mathematics behind machine learning and modern AI, linking ideas such as linear algebra and calculus to the technology’s development and limitations. Its narrative approach is aimed at readers seeking an accessible starting point, though customer feedback suggests the mathematical depth and readability may not suit everyone.
At a glance
- Explains mathematical foundations of machine learning, including linear algebra and calculus.
- Connects AI’s development to the history of mathematics, computer science and computing hardware.
- Discusses the influence of machine-learning systems and the limitations of AI.
Reference price: $79.99
Price checked: 13 Nov 2026
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Pros and cons
Pros
- A narrative introduction to the mathematics underpinning modern AI.
- The listed 480-page length allows room to cover historical context alongside mathematical ideas.
Technical specifications
9 specifications| Publisher | Allen Lane |
|---|---|
| Publication date | 15 October 2024 |
| Edition | 1st |
| Language | English |
| Print length | 480 pages |
| ISBN-10 | 0241586488 |
| ISBN-13 | 978-0241586488 |
| Weight listed | 700 g |
|---|---|
| Dimensions | 16.3 x 4 x 24.2 cm |
What to know before buying
- The description presents the mathematics as fundamental, but customer feedback is mixed on how clearly it is explained and whether the material goes beyond readers’ prior study. Consider your comfort with maths before choosing it as an introductory read.
Who is it for?
A good fit for
- Readers looking for a narrative introduction to the mathematical ideas behind machine learning.
- People interested in AI’s history and the limits of its applications.
Less suited to
- Readers seeking a practical coding manual or a maths-light overview. The listing describes mathematical content, and customer feedback indicates it may be demanding for some.
Customer reviews on Amazon
- 5 stars
74% 74% - 4 stars
19% 19% - 3 stars
4% 4% - 2 stars
1% 1% - 1 star
2% 2%
Customer feedback highlights the book as a useful starting point for understanding AI and appreciates its succinct writing. Opinions are mixed on both the mathematics and readability, with some finding the explanations clear and others finding the material beyond their background or not an easy read. That makes the book’s mathematical focus a key consideration for readers seeking an accessible introduction. The aggregate rating is mostly five-star, but ratings alone do not explain why readers differed.
Positive themes
- Customers appreciate its succinct writing and consider it a starting point for understanding AI.
Mixed feedback
- Feedback is divided on whether the mathematics is well explained or too advanced for some readers.
- Readability is mixed, with some finding it readable and others finding it difficult.
Frequently asked questions
What does Why Machines Learn cover?
It explores the mathematics behind machine learning and AI, with discussion of linear algebra, calculus, the technology’s historical development and its limitations.
Is this book suitable for someone new to AI?
Customer feedback describes it as a useful starting point for understanding AI. However, readers differ on the difficulty of the mathematics and the book’s readability, so it may not feel introductory to everyone.
What edition and format details are listed?
The listing gives a first edition in English with 480 pages. It does not specify a digital or audiobook format.
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