April 2017
Intermediate to advanced
320 pages
7h 46m
English
Content preview from Deep Learning with TensorFlow
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How does an artificial neural network learn?
The learning process of a neural network is configured as an iterative process of optimization of the weights, and is therefore of the supervised type. The weights are modified based on the network performance on a set of examples belonging to the training set, where the category they belong to is known. The aim is to minimize a loss function, which indicates the degree to which the behavior of the network deviates from the desired one. The performance of the network is then verified on a test set consisting of objects (for example, images in a image classification problem) other than those of the training set.
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