What is activation function tuning in neural networks?
Activation function tuning involves adjusting the parameters of activation functions to improve model performance.
Why is it important to tune activation functions?
Tuning activation functions can enhance learning efficiency, convergence speed, and overall model accuracy.
What are some common activation functions used in tuning?
Common activation functions include ReLU, Sigmoid, Tanh, and Softmax, each with unique properties.
How do I know if my activation function is well-tuned?
You can evaluate performance metrics like accuracy, loss, and training time to determine if tuning is effective.
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