Activation Functions in Neural Networks: A Guide
Introduction:
Activation functions play a vital role in neural networks, influencing their behavior and determining their ability to make accurate predictions. This article delves into the world of neural network activation functions, exploring their purpose, types, and factors to consider when selecting the right function.
Purpose of Activation Functions:
Activation functions serve two primary purposes in neural networks:
- Thresholding: They determine whether a neuron should be activated or not based on its weighted input. This allows neurons to make binary decisions, which are essential for tasks like classification.
- Non-Linearity: Activation functions introduce non-linearity into neural networks, making them capable of capturing complex relationships in data. This enables networks to learn intricate patterns and make accurate predictions.
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