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In context of a neural network, what is the purpose of using non - linear activation functions like RelU or Sigmoid? 1 ) To ensure
In context of a neural network, what is the purpose of using nonlinear activation functions like RelU or Sigmoid?
To ensure the model outputs are bounded
to avoid vanishing gradient issues
introduce nonlinearity into the model. allowing it to learn complex patterns
To maintain linearity throughout the network layers
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