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Activation Functions

Non-linear functions in neural networks

Allow strong signals through, block weak signals

Types:

sigmoid - binary classification
relu - image classification
softmax - multi-class output
tanh - NLP tasks

Provides non-linearity for artificial-neural-network

→ Enables learning complex patterns → Types: ReLU, sigmoid, tanh, softmax → Without it, network collapses to linear regression

References

Activation Functions in Neural Networks
Activation Functions Guide - DeepAI
Understanding Activation Functions - Towards Data Science #ml-notes
Comparative Study of Activation Functions

#ml-notes

Activation Function

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