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Jeff Heaton

Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms

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Descripción

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 is a book series meant to teach AI to those without an extensive mathematical background. The reader needs only a knowledge of basic college algebra or computer programming-anything more complicated than that is thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, R, Python and C. Other languages planned.

Detalles

Formato Tapa suave
Número de Páginas 224
Lenguaje Inglés
Editorial Createspace Independent Publishing Platform
Fecha de Publicación 2013-11-26
Dimensiones 9.25" x 7.52" x 0.47" pulgadas
Serie Artificial Intelligence for Humans
Letra Grande No
Con Ilustraciones No

Acerca del Autor

Jeff Heaton, PhD, is a computer scientist that specializes in data science and artificial intelligence. Specializing in Python, R, Java and C#, he is an 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).

Garantía & Otros

Peso0.86lb
SKU9781493682225
Publicado en Unimart.com22-01-25
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