[PDF.18yd] Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms

Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms

[PDF.bg36] Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms

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 | #75631 in Books |  2013-11-26 | Original language:English | PDF # 1 |  9.25 x.50 x7.50l,.86 | File type: PDF | 222 pages

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||19 of 21 people found the following review helpful.| A Basic Introduction to Machine Learning|By David Taylor|This book claims to be an overview of artificial intelligence, but it’s not; it’s an overview of machine learning. It’s true that machine learning is a hot topic within AI just now, but it's hardly taken over the field, nor has it rendered all other methods obsolete. But, if you just want an informal i|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

A great building requires a strong foundation. This book teaches basic Artificial Intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, Nelder Mead, and linear regression. These are not just foundational algorithms for the rest of the series, but are very useful in their own right. The book explains all algorithms using actual numeric calculations that you can perform yourself. Artificial Intelligence for Humans...

You easily download any file type for your gadget.Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms   |  Jeff Heaton. Just read it with an open mind because none of us really know.

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