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AI and Machine Learning Quiz

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

Which among the following is an application of AI?

a)

Computer Vision

b)

Natural Language Processing

c)

Decision Making

d)

All of the above

2.

The process of converting text to numbers is called

a)

Vectorization

b)

One-Hot Encoding

c)

Label Encoding

d)

TF-IDF

3.

The four 'V's of Big Data include

a)

Variety

b)

Volume

c)

Velocity

d)

All of the above

4.

Which of the following terms is not associated with Reinforcement Learning?

a)

Agent

b)

Environment

c)

State

d)

Return

5.

Which of these methods can be used to generalize a model?

a)

General

b)

Dropout

c)

Feature General

d)

Generalization

6.

A ____ algorithm will go through a neural network and adjust the weights of neural connections to correct errors.

a)

propagation

b)

forward propagation

c)

recursive

d)

back-propagation

7.

What of the following is a challenge for AI?

a)

Data Scarcity

b)

Algorithm Bias

c)

Difficulty in explaining results

d)

All of the above

8.

Deeper neural networks also yield better results when compared to shallower counterparts.

a)

True

b)

False

9.

During the times of COVID-19, which application of AI can help detect whether a person is wearing a mask or not?

a)

NLP

b)

Reinforcement Learning

c)

Computer Vision

d)

Decision Making

10.

Which of the following models would be appropriate for manipulating an image to imitate an artist's style?

a)

Reinforcement Learning

b)

GAN

c)

RNN

d)

LSTM

11.

Which of the following Python libraries is used for digital image processing?

a)

scikit-learn

b)

OpenCV

c)

TensorFlow

d)

pandas

12.

Suppose you are trying to build an AI to play the game of Chess. Which algorithm among the following would be appropriate?

a)

Linear Regression

b)

Q-learning

c)

Decision Trees

d)

GAN

13.

In a deep neural network for multi-class classification, which activation function should be used on the output neuron?

a)

Softmax

b)

Sigmoid

c)

ReLU

d)

Linear

14.

BERT makes use of _____ for its predictions

a)

Transformer

b)

Attention

c)

Both Transformer and Attention

d)

None of the above

15.

RNNs train using

a)

Back-propagation

b)

Back-propagation through layers

c)

Back-propagation through time

d)

Back-propagation through gradient

16.

The most important aspect to consider when looking for an AI-based solution is

a)

The issue being solved needs to be grounded in a clear-cut business problem

b)

Having a huge amount of data to work with

c)

Having enough resources to train the AI model

d)

Having many data scientists to work on the problem

17.

GAN comprises of

a)

Input Layer and Output Layer

b)

Generator and Discriminator

c)

Environment and Reward

d)

Producer and Consumer

18.

Which of the following is not an application of NLP?

a)

Language Translation

b)

Text auto completion

c)

Self Driving Cars

d)

Target Advertisement

19.

If AI does not eventually destroy humanity, the impact of AI on society will mean

a)

Overall decrease in jobs as everything will be done by machines

b)

Social impact similar to the Industrial Revolution. The fabric of society will be changed, not destroyed

c)

Humans won't have to do anything

d)

A peaceful society

20.

Which of the following is a common technique used to prevent overfitting in neural networks?

a)

Normalization

b)

Batch Processing

c)

Regularization

d)

Data Augmentation

21.

What is the primary purpose of the loss function in a neural network?

a)

To measure the accuracy of the model

b)

To calculate the gradient

c)

To optimize the weights of the model

d)

To evaluate the performance of the model

22.

Which of the following is a popular framework for building deep learning models?

a)

TensorFlow

b)

Scikit-learn

c)

Pandas

d)

NumPy

23.

What technique is commonly used to improve the performance of a neural network by reducing its complexity?

a)

Dropout

b)

Batch Normalization

c)

Data Normalization

d)

Feature Scaling

24.

Which of the following is a key advantage of using Convolutional Neural Networks (CNNs) for image processing tasks?

a)

They can automatically detect features

b)

They are easier to implement

c)

They require less data

d)

They are faster than traditional algorithms

25.

In the context of machine learning, what does the term 'hyperparameter tuning' refer to?

a)

Optimizing the learning rate

b)

Adjusting the model's architecture

c)

Choosing the best model from a set of candidates

d)

Fine-tuning the parameters of the model during training