In artificial neural networks(ANN), the activation function helps us to determine the output of Neural Network. They decide whether the neuron should be activated or not. It determines the output of a model, its accuracy, and computational efficiency.

Single neuron structure. source wiki.tum.de
Single neuron structure. source wiki.tum.de
Single neuron structure. Source wiki.tum.de

Inputs are fed into the neurons in the input layer. Inputs(Xi) are then multiplied with their weights(Wi) and add the bias gives the output(y=(Xi*Wi)+b) of the neuron. We apply our activation function on Y then it is transfer to the next layer.

Properties that Activation function should hold?

Vivek patel

Data Scientist at Kushagramati. Keen interest in Machine Learning | Deep learning | NLP | Computer Vision practitioner.

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