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Why Machines Learn

The Elegant Maths Behind Modern AI

145 Lesepunkte
Taschenbuch
Taschenbuch
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'An invaluable companion for anyone who wants a deep understanding of what's under the hood of often inscrutable machines' Melanie Mitchell

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence

Machine-learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether someone gets bail. They now influence discoveries in chemistry, biology and physics - the study of genomes, extra-solar planets, even the intricacies of quantum systems.

We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. It took the development of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see all around us today. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules.

As Ananthaswamy resonantly concludes, to make the most of our most wondrous technologies we need to understand their profound limitations - the clues lie in the maths that makes AI possible.

Produktdetails

Erscheinungsdatum
28. August 2025
Sprache
englisch
Seitenanzahl
480
Autor/Autorin
Anil Ananthaswamy
Verlag/Hersteller
Produktart
kartoniert
Gewicht
500 g
Größe (L/B/H)
198/129/35 mm
Sonstiges
B-format paperback
ISBN
9781802060867

Portrait

Anil Ananthaswamy

Anil Ananthaswamy is an award-winning science writer and former staff writer and deputy news editor for New Scientist. He is the author of several popular science books including The Man Who Wasn't There, which was long-listed for the Pen/E. O. Wilson Literary Science Writing Award. He was a 2019-20 MIT Knight Science Journalism Fellow and the recipient of the Distinguished Alum Award, the highest award given by IIT-Madras to its graduates, for his contributions to science writing.

Pressestimmen

After just a few minutes of reading Why Machines Learn, you'll feel your own synaptic weights getting updated. By the end you will have achieved your own version of deep learning - with deep pleasure and insight along the way Steven Strogatz

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