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Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms Paperback – 26 Nov 2013

3.1 out of 5 stars 7 customer reviews

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  • Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms
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  • Artificial Intelligence for Humans, Volume 2: Nature-Inspired Algorithms
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  • Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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Product details

  • Paperback: 222 pages
  • Publisher: CreateSpace Independent Publishing Platform; 1 edition (26 Nov. 2013)
  • Language: English
  • ISBN-10: 1493682229
  • ISBN-13: 978-1493682225
  • Product Dimensions: 19 x 1.3 x 23.5 cm
  • Average Customer Review: 3.1 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon Bestsellers Rank: 86,340 in Books (See Top 100 in Books)
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Product description

About the Author

Jeff Heaton, PhD, is a data scientist and indy publisher. Specializing in Python, R, Java and C#, he is an active technology blogger, open source contributor, and author of more than ten books. His areas of expertise include predictive modeling, data mining, big data, business intelligence, and artificial intelligence. Jeff holds a Master’s Degree in Information Management from Washington University and a PhD in computer science from Nova Southeastern University in computer science. He is the lead developer for the Encog Machine Learning Framework open source project, a senior member of IEEE, and a fellow of the Life Management Institute (FLMI).


Customer Reviews

3.1 out of 5 stars
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Top Customer Reviews

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It's hard to believe that Jeff Heaton has written code that anyone has had to work with or read for anything else than an exercise. Even the latter should mean that he writes code that should be readable and easy to follow, and more importantly actually correct, but such is not the case. Very little care was given to the code quality of this book, and it hurts the examples in it. They are suitable only for bad C/C++ code and if you are looking for examples with useful abstractions in them you would do well in completely skipping this book.

The part about equilateral encoding is especially painful and will leave even the most patient of readers annoyed. Heaton is the archetypical shitty coder that will use one-letter variables that represent important parts of a formula without explaining them. The part mentioned above also uses uninitialized variables with one-letter names, as if to further confuse readers.

There are a few paragraphs of text interspersed with the code that are, I assume, supposed to shed light on what is happening, but they rarely actually augment the meaning of the code or what is supposed to be happening.

This is not a good book for anyone but people who already know the material and simply want to refresh or confirm knowledge. I'm quite sure that the material is correct in scope, but it does not do a close to decent job in explaining stuff and uses downright bad code for most things in it.

All in all I think the book could have been served well by having Heaton define functions that were smaller in scope and had well defined purposes. They could then be used as abstractions (that have been well explained) and would lead to cleaner examples.
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Format: Paperback
To started with I hated this book - I almost tore it up - but then I liked it a bit.. then I liked it a lot.

This book is in sore need of some editing: there are a lot of grammar errors some of which make some of the explanations difficult to decipher. In some cases I had to resort to Google to untangle some terminology.

BUT...

For some one who :
- is starting from scratch with AI;
- can already programme; and
- who has some maths (age 18)

the book is a perfect run thru of the basic principles patterns and terminology of AI. It does a wonderful job of ordering the introduction of concepts so that they build on each other, by small increments, in a logical way so that you are hardly aware of the transition from trivial to profound.

The book identifies key pragmatic abstractions and, despite, the unpolished drafting, does the priceless task of identifying the core of simplicity around which complexity can later be built.

The book is self published and the guy clearly edited himself which goes to show how important an objective view can be. He would really have benefited from some hard talking.

Despite this however, the fundamental cleverness and appropriateness of the approach provides a succinct introduction to the subject.
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Format: Paperback Verified Purchase
These books seems to be written more by a hobbist than a professional. They often say the same basic things several times, they lack depth, and lack inspriational applications. I don't recomend them to anyone. Sorry.
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It has a really nice old-school eighties programming feel and I like it a lot .. I had to work a bit to get the Java compiler and programs running .. but am now enjoying working through well presented ideas..
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