Top AI books curated by experts

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification.

The alignment problem describes the problems associated with building powerful artificial intelligence systems that are aligned with their operators. The concept was popularised by Brian Christian in his book The Alignment Problem: Machine Learning and Human Values

A historical study of Chile's twin experiments with cybernetics and socialism, and what they tell us about the relationship of technology and politics. In Cybernetic Revolutionaries, Eden Medina tells the history of two intersecting utopian visions, one political and one technological.

In this richly illustrated book, key neural network learning algorithms are explained informally first, followed by detailed mathematical analyses. Topics include both historically important neural networks (e.g. perceptrons), and modern deep neural networks (e.g. generative adversarial networks…

The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning).

"The Singularity Is Near" portrays what life will be like after this event? a human-machine civilization where our experiences shift from real reality to virtual reality and where our intelligence becomes nonbiological and trillions of times more powerful than unaided human intelligence.

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

“Artificial Intelligence: A Modern Approach” goes beyond the basics and delves into advanced topics in AI. It covers natural language processing, an area concerned with enabling computers to understand and generate human language. The book explores techniques for parsing, semantic analysis, and …

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award‑winning scholar Kate Crawford reveals how AI is a technology of extraction: from the mi…

Reinforcement learning is an autonomous, self-teaching system that essentially learns by trial and error. It performs actions with the aim of maximizing rewards, or in other words, it is learning by doing in order to achieve the best outcomes.

Artificial Intelligence: A Guide for Thinking Humans is a 2019 nonfiction book by Santa Fe Institute professor Melanie Mitchell. The book provides an overview of artificial intelligence (AI) technology, and argues that people tend to overestimate the abilities of artificial intelligence.

Something new entered our world in November 2022 — the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on ou…

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts…

In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the lea…