Tag: sigmoid activation function
Difference between Sigmoid and Softmax activation function?
Sigmoid activation function is a type of logistic activation function. It is used in the hidden layers of neural networks to transform the linear output into a nonlinear one. Softmax activation function is used in the output layer of neural networks to convert the linear output into a probabilistic one. Sigmoid activation functions are used…
Read MoreWhat is ReLU and Sigmoid activation function?
The activation function is a nonlinear function that takes in the weighted sum and produces the output. They are used to provide a more simplified model of neuron behavior which can be used as an input to deep neural networks. There are many different activation functions that can be used, including sigmoid, hyperbolic tangent, logistic,…
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