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Explain Activation Function in Neural Network and its types.

Ans: It is a Function used in Neural Network in order to calculate weighted sum and add bias with it. It also introduces non-linearity into output of a Neuron. Back Propagation is possible in Neural network by using Activation Function since the gradients are provided along with error to update the weights and biases. Due to no-linear transformation of input caused by Activation Function makes the Neural Network capable of Learning and Performing Complex tasks.

Different types of Activation Functions:

  • Binary Step
  • Linear Activation
  • Sigmoid/ Logistic
  • Tanh / Hyperbolic Tangent
  • ReLU (Rectified Linear Unit)
  • Leaky ReLU
  • Parametric ReLU
  • Softmax
  • Swish

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