Deep Learning: Activation Functions Quiz (Easy)

What is the primary purpose of activation functions in deep learning?

Which activation function is known for addressing the vanishing gradient problem?

Which activation function is bounded between -1 and 1, making it useful for models where the output needs to be within a specific range?

Which activation function is often used in the output layer of a multi-class classification neural network to produce class probabilities?

Which activation function is commonly used for binary classification tasks, as it maps the output to values between 0 and 1?

Which activation function is often used in the output layer of a neural network for regression tasks?

The Leaky ReLU activation function is an improved version of the ReLU function. What does it add to the standard ReLU?

In which type of neural network is the Softmax activation function typically used in the output layer?

In the context of the Leaky ReLU activation function, what does the parameter ‘α’ control?

What does the Softmax activation function do in a neural network?

When using the Rectified Linear Unit (ReLU) activation function, what can be done to mitigate the problem of “dead” neurons?