Neural Networks
How do activation functions affect neural network learning and performance?
Answer:
Activation functions are fundamental in neural networks because they introduce non-linearity, enabling accurate modelling of complex data patterns. Functions such as ReLU, sigmoid, and softmax support tasks ranging from efficient training to classification and prevent models from behaving as linear alternatives.
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