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Neural Networks and Deep Learning Quiz

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is the key to the success of artificial neural networks?

a)

Their lack of mathematical calculations

b)

Their simplicity

c)

Their ability to work without data

d)

Their hidden layers

2.

What dataset was created to help AI recognize images?

a)

AIImageDB

b)

VisionSet

c)

PhotoNet

d)

ImageNet

3.

What is the purpose of the input layer in a neural network?

a)

To perform all the mathematical calculations

b)

To store the output probabilities

c)

To make the final decision

d)

To receive data represented as numbers

4.

What does each neuron in the hidden layer do?

a)

Decides the final answer

b)

Deletes unnecessary data

c)

Stores the final output

d)

Mathematically combines all the numbers it gets

5.

What is the output layer responsible for in a neural network?

a)

Combining the outputs of the hidden layers to answer the problem

b)

Receiving the input data

c)

Training the network

d)

Deleting incorrect answers

6.

What was the name of the neural network created by Alex Krizhevsky?

a)

DeepNet

b)

AlexNet

c)

ImageNet

d)

VisionNet

7.

What is the main challenge of using deeper neural networks?

a)

They are less accurate

b)

They require more computational power

c)

They are easier to understand

d)

They do not need training

8.

What is the role of weights in a neural network?

a)

To determine the importance of inputs

b)

To store the final output

c)

To delete unnecessary data

d)

To simplify the network

9.

What is the purpose of crowd-sourcing in creating datasets like ImageNet?

a)

To simplify the dataset

b)

To label data efficiently by spreading the work among many people

c)

To train neural networks

d)

To delete incorrect data

10.

What is one of the main applications of neural networks mentioned in the text?

a)

Designing websites

b)

Creating video games

c)

Building physical robots

d)

Fraud detection in banks