can be any non-linear differentiable function like sigmoid, tanh, ReLU, etc. (commonly used in the deep learning community). Learning in neural networks is nothing but finding the optimum weight ...

Deep learning is a form ... actually have smooth activation functions, such as the logistic or sigmoid function, the hyperbolic tangent, and the Rectified Linear Unit (ReLU).

It has components that support deep learning, linear algebra ... For example, some CUDA function calls need to be wrapped in checkCudaErrors() calls. Also, in many cases the fastest code will ...