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Nature can be a great source of inspiration for artificial intelligence algorithms because its technology is considerably more advanced than our own. Among its wonders are strong AI, nanotechnology, and advanced robotics. Nature can therefore serve as a guide for real-life problem solving. In this book, you will encounter algorithms influenced by ants, bees, genomes, birds, and cells that provide practical methods for many types of AI situations. Although nature is the muse behind the methods, we are not duplicating its exact processes. The complex behaviors in nature merely provide inspiration in our quest to gain new insights about data. Artificial Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. No knowledge of biology is needed to read this book. With a forward by Dave Snell.
| Book 2 Of 3 | Artificial Intelligence for Humans |
| Dimensions | 7.5 x 0.55 x 9.25 inches |
| Isbn 10 | 1499720572 |
| Isbn 13 | 978-1499720570 |
| Item Weight | 1.05 pounds |
| Language | English |
| Print Length | 242 pages |
| Publication Date | May 28, 2014 |
| Publisher | CreateSpace Independent Publishing Platform |
User
Another good one.
Haven't made it all the way through this yet, but figured I'd leave a review. The foreword states that you can read these books in any order. The author makes these topics interesting so I feel like it's all worth a read even if you're not interested in things like genetic algorithms.
User
Great for understanding AI terms and concepts without a math background
I really like this series. I read Artificial Intelligence for Humans, Volume 1 and then ordered volumes 2 and 3. What I like about this series is the same thing I like about Volume 2, that it's very readable. For someone without a math background, and limited programming prowess, I can understand the concepts. The only things about the book that I don't like are:1) Some of the context is missing. For instance, I can understand Genetic Algorithms, Partical Swarm Optimization, and Ant Colony Optimization as concepts and I think I could basically code them if I needed to. I would say his forte is explaining the ideas and the math in plain language. But I don't quite understand from the book how to tie them back into training an RBF Network. His descriptions of each concept is really easy to grasp onto. But I find myself missing the overall picture of how things fit together.2) There are some weird formatting things like the spread you see in the photo.Anyway, if you can put the context in place and you don't mind the self-published formatting, I think you'll like the book... Especially if you don't have a math background but are still interested in AI.
User
Not very good!!
It offers a lot of items but I doesn't explain very well each one of them.
User
in good shape, as described
The items were delivered on time, and the books are new, in good shape, as described.
User
Five Stars
I love Jeff Heaton books. They are very clear to understand
User
very useful
concise and clear
User
Five Stars
Excellent product
User
Very superficial descriptions, code almost non-existent. Waste of time and money
I feel bad giving such a low review, but this book really is a waste of time.I had seen articles about this subject before, and had played around a little with the algorithms, and was looking for something to explain the algorithms in more depth, and guide me as to how to write code.This book fails miserably at all of that. He gives a very high level overview of the algorithm, not really enough to get the point, then if you're lucky, gives some pseudocode, which is actually a very cut down Python script that doesn't have enough code to tell you much, then says "By running this code I got the following results..." without anything in between. The only way to see what the code does is to download the source and read it yourself. I don't need to buy his book to do that, there are plenty of online bits of code I can download for free. What I wanted was something that would explain the code, which this doesn't. If I hadn't had any previous background to the material, I wouldn't have got anywhere from his scant explanations.If you're interested in this sort of subject, I recommend you read some of the articles by James Mccaffrey (regular columnist in MSDN Magazine , search online and you'll find his articles) which cover these subject much more clearly. He gives an explanation of the algorithm (like one you can understand and has enough detail to tell you were you're going), shows enough code so you can see how he's implemented it, without distracting you with all the little details, then explains the output. You can also download the code and go into it in more detail. The code is in C#, but he deliberately writes very plain C#, which is almost identical to the equivalent Java, and very readable for a Python programmer. Once you've got going with that, the next best thing to do is ask questions on Stack Exchange where you'll get no end of help.In summary, I really can't recommend this book at all.
User
Sur la lancée du premier volume
Comme le premier volume, un ouvrage clair avec des exemples détaillés. Algorithmes génétiques, comportements de troupeau, des outils indispensables à l'IA.
User
Leicht verständliche Lektüre zum Thema Künstliche Intelligenz. Band 2 mit genetischen Algorithmen.
Die Bücher sind in englischer Sprache verfasst, aber leicht verständlich, sofern man der englischen Sprache mächtig ist.Band 2 gibt einen guten Überblick über genetische Algorithmen und Konzepte im Kontext KI.Die Themen sind recht knapp, jedoch ausreichend beschrieben, sofern man einigermaßen mit der Materie vertraut ist.Gut gefällt mir, dass viele Bilder und anschauliche Beispiele verwendet werden, um die Themen verständlicher zu präsentieren.Oft zeigt der Autor sogar Pseudo-Code-Schnippsel, so dass man direkt Ideen für die Implementierung erhält.Top ist auch, dass online zu allen Kapiteln fertige Implementierungen in einigen Programmiersprachen (Java, Python etc.) zu finden sind (links im Buch).Ich habe mir alle drei Bände als Ebooks gekauft. Im Vergleich zu den Printbüchern ein Schnäppchen.*** Fazit ***Hilfreiche Lektüre, wenn man sich intensiver mit dem Thema KI beschäftigen möchte. 5 Sterne für Inhalt, Struktur und Verständlichkeit.War meine Rezension hilfreich? Wenn ja, dann würde ich mich über einen kurzen Klick auf "ja - hilfreich" sehr freuen.
User
Five Stars
Very instructive set of books, with a practical perspective.
User
Tutto OK
Tutto OKTutto OK
User
Great
Great book!
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