What happens to a neural network with linear activations in all layers except the last one with a sigmoid activation?
Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required Exercise Solutio

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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
It becomes a support vector machine.
It collapses into a single linear layer followed by a sigmoid, resembling logistic regression.
It functions as a linear regression model.
It becomes a deep neural network.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is logistic regression not typically called a neural network?
Because it uses a different type of activation function.
Because it lacks multiple layers with non-linear activations.
Because it is only used for regression tasks.
Because it is a type of decision tree.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary function of logistic regression?
To reduce dimensionality.
To predict continuous values.
To classify data points.
To perform clustering.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Under what condition does a model become a neural network?
When it is trained using backpropagation.
When it has a single layer with linear activation.
When it includes non-linear activations in any of the hidden layers.
When it uses a sigmoid activation in the output layer.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of non-linear activations in a neural network?
They are used only in the output layer.
They allow the network to perform linear transformations.
They enable the network to model complex patterns.
They simplify the network architecture.
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