Artificial Intelligence for Humans: Deep learning and neural networks.
By: Heaton, Jeff
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Material type: 
BookPublisher: St.Louis : Heaton Research, 2015Description: xlviii, 323p.ISBN: 9781505714340.Subject(s): Algorithms | Artificial intelligence | Neural networks (Computer science)Online resources: Click here to access online Summary: 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.
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Ziauddin Faculty of Engineering, Sciences, Technology & Management Library - N On Display | Q335 HEA 2015 (Browse shelf) | Available | 18399 |
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.
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