Posted inTechnology Insights
Fonction d’activation neuronale
Softmax softmax(xᵢ) = eˣⁱ / ∑eˣʲ Used for multi-class classification. Outputs probability distribution.
Posted inTechnology Insights
Fonction d’activation neuronale
ReLU ReLU(x) = max(0, x) Most popular. Computationally efficient, helps with vanishing gradient problem.
Posted inTechnology Insights
Fonction d’activation neuronale
Tanh tanh(x) = (eˣ - e⁻ˣ) / (eˣ + e⁻ˣ) Output range: (-1, 1). Zero-centered, often better than sigmoid.
Posted inTechnology Insights
Fonction d’activation neuronale
Sigmoid σ(x) = 1 / (1 + e⁻ˣ) Output range: (0, 1). Used for binary classification and probability outputs
Posted inTechnology Insights
Roman number
However, the numeral for four is not IIII. Instead, the number four is written as IV.
