Artificial intelligence for humans. Volume 3, Deep learning and neural networks
General Material Designation
[Book]
First Statement of Responsibility
Jeff Heaton.
EDITION STATEMENT
Edition Statement
Edition 1.0
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
St. Louis, MO
Name of Publisher, Distributor, etc.
Heaton Research, Inc.
Date of Publication, Distribution, etc.
2015
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xlix, 323 pages : illustrations ; 24 cm
SUMMARY OR ABSTRACT
Text of Note
Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We examine current neural network technologies, including ReLU activation, stochastic gradient descent, cross-entropy, regularization, dropout, and visualization. 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 provided in Java, C#, and Python.--Back cover.