January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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ReLU
The Rectified Linear Unit (ReLU) has become quite popular in recent years. Its mathematical formula is as follows:
Compared to sigmoid and tanh, its computation is much simpler and more efficient. It was proved that it improves convergence by six times (for example, a factor of 6 in Krizhevsky and it's co-authors in their work of ImageNet Classification with Deep Convolutional Neural Networks, 2012), possibly due to the fact that it has a linear and non-saturating form. Also, unlike tanh or sigmoid functions which involve the expensive exponential operation, ReLU can be achieved by simply thresholding activation at zero. Therefore, it ...
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