Artificial intelligence is the hottest tech topic there is at the moment. It is therefore not surprising that there are hundreds of books available on. A list of 17 new artificial intelligence books you should read in , such as The WEIRD CEO, The AI Advantage and Will Computers Revolt. Find our list of the best books on artificial intelligence, machine learning and robotics for beginners and pros. Choose yours, read and meet the.

Artificial Intelligence Book

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Here are some of the best books on the rich history, rabid speculations and intriguing fictionalized world of artificial intelligence. Online shopping for Artificial Intelligence from a great selection at Books Store. Discover the best Artificial Intelligence in Best Sellers. Find the top most popular items in site Books Best Sellers.

So one can probably claim, not without justification, that AIMA emphasizes Bayesian probability over other approaches. Finally, as good as AIMA is, it is still a survey. Even with respect to Bayesian probability, the treatment is introductory, as I discovered with some shock upon reading Probability Theory: The Logic of Science.

That's OK, though: So read it once for the survey, keep it on your shelf for the bibliography, and refer back to it whenever you find yourself thinking "hey, didn't I read about that somewhere before? Dec 25, Mohammed rated it it was amazing. Aug 06, Carl rated it it was amazing Shelves: For a textbook, this is amazingly accessible and interesting. Jun 07, A. Mignan rated it it was amazing Shelves: The Bible on computational decision-making.

Top 15 Best Books on Artificial Intelligence – Programming, Robotics, ML

This textbook tends to perfection, with no stone left unturned. Looking forward to the next edition, which, at the accelerating rate of innovation, looks overdue the following sentence surely feels outdated: T The Bible on computational decision-making.

There are 2 aspects I particularly enjoyed, 1 the historical sections at the end of each chapter; the introduction also gave a fascinating history of AI and its relationship to other fields neurology, logics, cybernetics…. I truly wish I had discovered that book when it was first published in , sigh Sep 02, Erik rated it liked it. OK so I did not read this cover to cover, but I did look closely at much of what you might call the foundational chapters, just to see 1.

Goal 2 was much more important as I teach a logic of induction class and of course one major pillar of AI would be developing machines that can perform judgments under uncertainty and apply rational heuristics as well as OK so I did not read this cover to cover, but I did look closely at much of what you might call the foundational chapters, just to see 1.

Goal 2 was much more important as I teach a logic of induction class and of course one major pillar of AI would be developing machines that can perform judgments under uncertainty and apply rational heuristics as well as humans do which is not very well at all by the way.

I found out that I already knew most of this, from studies of Bayesian reasoning which is very tricky by the way and should not be blindly implemented like this without a clear view of the limitations , and the study of acyclic causal graphs which is standard academy reading for philosophers.

These graphs also admit of howlers and counterexamples as anyone knows. I am more interested in the idea of developing "stupid machines" that function more like neural networks and less like probability maximizers. The human brain is fundamentally in my view anyway a stupid-machine, full of crazy workarounds and faulty logic. The correct solution or path is virtually never the one evolution comes up with, it just grinds it out with massive armies of neurons and interconnections and lots of trial and error, but nothing one would call a computation, as in Turing machines.

Elegant algorithms for computer vision have, I believe, nothing to do with the way the brain constructs the visual image.

One philosopher's take. Dec 19, Arjun rated it it was amazing Shelves: A fantastic textbook that's not only a great introduction to AI but also serves as a survey course in technical writing. Re-reading some earlier chapters taught me how much I missed on a first read or forgot.

The first 10 chapters or so are the A fantastic textbook that's not only a great introduction to AI but also serves as a survey course in technical writing. The first 10 chapters or so are the best and the second half of the book can be a bit of a trudge as it devolves into mathematical masturbation.

A lot of the chapters are better served by other resources — I highly recommend the CS lectures from UC Berkeley for supplementation. Unfortunately, some chapters are straight up bad the chapter on Philosophical Foundations comes to mind , but these tend to be few and far between. Despite that, there is no more comprehensive book on AI.

Read this, re-read this, and treat it with care — you will reap the rewards for a long time to come. Jul 01, Luis rated it liked it Shelves: A bit boring. Lacks good solved exercises. Very short on detail in some areas such as Neural Networks. Very "theoretical". However it does provide a good theoretical introduction to many subjects.

I liked the chapters on search. Mar 07, Nakosy rated it really liked it. It was written more like a text book for undergrads with extensive coverage of many topics. However, I was looking for more in-depth information on knowledge representation.

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But, it was too superficial for my need. May be, in 3rd edition it encompassed the latest ideas in this area. Dec 17, Drew rated it really liked it Shelves: A comprehensive course in modern AI topics. While the book is dense with information, the authors provide clear explanations that will be easily picked up by the careful reader. An excellent companion to an undergraduate course in artificial intelligence. Jan 05, James Ravenscroft rated it it was amazing Shelves: This is THE book to read on anything to do with modern artificial intelligence.

I regard this as my personal bible and would recommend it to anyone who is involved in technical artificial intelligence.

Um excelente livro para quem quer estudar fundamentos de IA, recomendo. Great overview over such a big and complex field such as Artificial Intelligence. Mar 01, Jaslyn rated it it was amazing. Mar 23, Shahriar Hossain is currently reading it.

We call ourself Homo sepiens - man the wise This is the most complete and comprehensive book I read on a subject of Artificial Intelligence so far and it's very well written as well. If you plan diving into AI really seriously and you are keen to invest some good amount of time going through pages of this book then I really recommend it for you. Great addition to this book is A.

Best Books on Artificial Intelligence for Audio Learners

Last three months I spent every day with both this book and A. It's a pricey book. It was used in my university on AI. It covers many AI topics including intelligent agents, searching, knowledge representation, machine learning, etc.

There are enough examples, but not enough good and clear examples. In spite of all that, though, it's still a very good book, and a good overview of the field.

I particularly liked that each chapter had an extensive section with historical and biographical notes at the end. If nothing else, it at least demonstrates that if the AI winter was ever a real thing at least in terms of research activity and progress , it's far behind us now. Artificial Intelligence is, in the context of the infant science of computing, a very old and very broad subdiscipline, the "Turing test" having arisen, not only at the same time, but from the same person as many of the foundations of computing itself.

Those of us students of a certain age will recall terms like "symbolic" vs. In short, a major challenge facing anyone wishing to survey Artificial Intelligence is simply coming up with a unifying theme.

The major accomplishment, in my opinion, of AIMA, then, is that: Russell and Norvig take the hodge-podge of AI research, manage to fit it sensibly into a narrative structure centered on the notion of different kinds of "agents" not to be confused with that portion of AI research that explicitly refers to its constructs as "agents!

It's up to the reader whether to follow the arcs of the stone from major subject to major subject, foregoing depth, or whether to pick a particular contact point and concentrate on the eddies propagating from it. Environmental Studies.

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Software Engineering. Agile Development.But his book is very rigorous in setting out a lot of the objections to his ideas and then tackling them. The author of the book will lead you through everything you need to know about algorithms in machine learning. If you are the interviewee and would like to update your choice of books or even just what you say about them please email us at editor fivebooks.

Librarian Note: We've come a long way from a 15th-century automaton knight crafted by Leonardo da Vinci. Deals and Shenanigans. Paths, Dangers, Strategies by Nick Bostrom.

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