Why Machines Learn

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.

Some books about the development of neural networks describe the underlying mathematics while others describe the social history. This book presents the mathematics in the context of the social history. It is a masterpiece. The author is very good at explaining the mathematics in a way that makes it available to people with only a rudimentary knowledge of the field, but he is also a very good writer who brings the social history to life.
Geoffrey Hinton, deep learning pioneer, Turing Award winner, former VP at Google, and Professor Emeritus at University of Toronto

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, New York Times bestselling author of Infinite Powers and professor of mathematics at Cornell University

If you were looking for a way to make sense of the AI revolution that is well underway, look no further. With this comprehensive yet engaging book, Anil Ananthaswamy puts it all into context, from the origin of the idea and its governing equations to its potential to transform medicine, quantum physics and virtually every aspect of our life. An essential read for understanding both the possibilities and limitations of artificial intelligence.
Sabine Hossenfelder, physicist and New York Times bestselling author of Existential Physics: A Scientist's Guide to Life's Biggest Questions

Why Machines Learn is a masterful work that explains in clear, accessible, and entertaining fashion the mathematics underlying modern machine learning, along with the colorful history of the field and its pioneering researchers.  As AI has increasingly profound impacts in our world, this book will be an invaluable companion for anyone who wants a deep understanding of what s under the hood of these often inscrutable machines.