What is the primary purpose of using activation functions in neural networks?

To add complexity to the model
To control the learning rate
To introduce non-linearity in the model
To speed up the training process

The primary purpose of activation functions in neural networks is to introduce non-linearity into the model. Without non-linearity, neural networks would reduce to linear regression models, limiting their ability to learn complex patterns in data. Activation functions enable neural networks to approximate complex functions and make them suitable for a wide range of tasks.

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