Название: Matlab Neural Network Toolbox User's GuideАвтор: Mark Hudson Beale, Martin T. Hagan, Howard B. Demuth
Издательство: The MathWorks, Inc
Год: 2018
Страниц: 558
Язык: английский
Формат: pdf (true)
Размер: 10.17 MB
The book presents the theory of neural networks, discusses their design and application, and makes considerable use of the MATLAB environment and Neural Network Toolbox software. Example programs from the book are used in various sections of this documentation.
Deep learning is a branch of machine learning that teaches computers to do what comes naturally to humans: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. Deep learning is especially suited for image recognition, which is important for solving problems such as facial recognition, motion detection, and many advanced driver assistance technologies such as autonomous driving, lane detection, pedestrian detection, and autonomous parking.
Neural Network Toolbox provides simple MATLAB commands for creating and interconnecting the layers of a deep neural network. Examples and pretrained networks make it easy to use MATLAB for deep learning, even without knowledge of advanced computer vision algorithms or neural networks.
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