This property is required to compute the gradients which allows us to tune the network weights. To allow backpropagation through the network, the selected activation function should be differentiable. and is effective only up to a single layer. no activation function) is unable to make sense of complicated data, such as, speech, videos, etc. On the other hand, a model which uses a linear function (i.e. Non-linearity means that the output cannot be replicated from a linear combination of inputs this allows the model to learn complex mappings from the available data, and thus the network becomes a universal approximator. It allows us to model a class label or score that varies non-linearly with independent variables. ![]() An activation function is used to introduce non-linearity in an artificial neural network.
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