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Activation functions add non-linearity, enabling neural networks to learn complex patterns. If you explore AI machine learning courses, you’ll frequently study these functions in depth because they determine how signals flow through a network.
Common types:
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ReLU: fast, widely used
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Sigmoid: for binary output
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Softmax: for multi-class output
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Tanh: outputs between –1 and 1
Without activation functions, a neural network becomes just a linear regression model.
Topic starter
Posted : 19/11/2025 6:01 am