activation functions
[ˌæk.tɪ.ˈveɪ.ʃən ˈfʌŋk.ʃənz]
nounpl: activation functions
funções de ativação
1. Mathematical functions used in artificial neural networks that determine the output of a neuron based on its input, introducing non-linearity to enable networks to learn complex patterns
ReLU and sigmoid are common activation functions used in deep learning models.
ReLU e sigmoid são funções de ativação comuns usadas em modelos de aprendizado profundo.
2. Functions that control whether a neuron should be activated or remain inactive based on the weighted sum of inputs
The choice of activation function significantly impacts the training speed and accuracy of neural networks.
A escolha da função de ativação impacta significativamente a velocidade de treinamento e a precisão das redes neurais.
This is a specialized technical term from machine learning and artificial intelligence that is used identically in both Brazilian Portuguese and international contexts. The term is widely understood in Brazilian tech communities, universities, and tech companies in São Paulo and Rio de Janeiro where AI development thrives.
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