Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required Exercise Solutio

Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required Exercise Solutio

Assessment

Interactive Video

Information Technology (IT), Architecture, Mathematics

University

Hard

Created by

Quizizz Content

FREE Resource

The video tutorial explores the concept of neural networks with linear activations and a single sigmoid-activated neuron in the last layer. It explains how such a structure collapses into a linear layer followed by a sigmoid, resembling logistic regression. The tutorial clarifies that logistic regression is not typically considered a neural network, despite its perceptron-like structure. It concludes that introducing non-linear activations in hidden layers transforms the model into a neural network.

Read more

5 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens to a neural network with linear activations in all layers except the last one with a sigmoid activation?

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.