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Artificial Intelligence: A Guide for Thinking Humans is a 2019 nonfiction book by Santa Fe Institute professor Melanie Mitchell. [1] The book provides an overview of artificial intelligence (AI) technology, and argues that people tend to overestimate the abilities of artificial intelligence. [2] [3]
Paradigms of AI Programming: Case Studies in Common Lisp (ISBN 1-55860-191-0) is a well-known programming book by Peter Norvig about artificial intelligence programming using Common Lisp. History [ edit ]
Artificial intelligence textbooks (3 P) Pages in category "Non-fiction books about Artificial intelligence" The following 23 pages are in this category, out of 23 total.
AIMA gives detailed information about the working of algorithms in AI. The book's chapters span from classical AI topics like searching algorithms and first-order logic, propositional logic and probabilistic reasoning to advanced topics such as multi-agent systems, constraint satisfaction problems, optimization problems, artificial neural networks, deep learning, reinforcement learning, and ...
The book outlines five approaches of machine learning: inductive reasoning, connectionism, evolutionary computation, Bayes' theorem and analogical modelling.The author explains these tribes to the reader by referring to more understandable processes of logic, connections made in the brain, natural selection, probability and similarity judgments.
In the fall of 2018, fast.ai released v1.0 of their free open-source library for deep learning called fastai (without a period), sitting atop PyTorch. Google Cloud was the first to announce its support. [6] This open-source framework is hosted on GitHub and is licensed under the Apache License, Version 2.0. [7] [8]
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Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]
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