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Week 6: Text features for Sentiments

Total questions: 86

Worksheet time: 1hrs 20mins

Name
Class
Date
1.
What is one similarity between artificial and biological neurons?
a)
Both process inputs to give an output
b)
Both can think on their own
c)
Both store memories
d)
Both are found in living beings
2.
What does the hidden layer in a neural network do?
a)
It provides input to the system
b)
It stores the final output
c)
It is visible to the user
d)
It processes data between input and output
3.
What is the role of the input layer in a neural network?
a)
To calculate weights
b)
To provide output
c)
To receive data from the user
d)
To generate features
4.
What does the output layer in a neural network represent?
a)
Hidden patterns
b)
Data received from the user
c)
Intermediate processing steps
d)
Final results of the network
5.
What are weights in a neural network?
a)
Filters for inputs
b)
Data inputs
c)
Numbers that represent layers
d)
Values that determine the importance of inputs
6.
What do filters do in neural networks?
a)
Store data
b)
Extract important features
c)
Provide output directly
d)
Define network architecture
7.
What does sentiment analysis help detect?
a)
Word length
b)
Grammar mistakes
c)
Sentence structure
d)
Emotions like happiness or anger
8.
What is the goal of feature extraction in text processing?
a)
To make sentences longer
b)
To create new words
c)
To identify key patterns or words
d)
To simplify sentences
9.
Which is an example of a feature for text analysis?
a)
Word frequency
b)
Font size
c)
Background color
d)
File type
10.
Which of these emotions can sentiment analysis detect?
a)
Confusion
b)
Complexity
c)
Sadness
d)
Focus
11.
What is one similarity between artificial and biological neurons?
a)
Both can think on their own
b)
Both store memories
c)
Both are found in living beings
d)
Both process inputs to give an output
12.
What does the hidden layer in a neural network do?
a)
It stores the final output
b)
It provides input to the system
c)
It is visible to the user
d)
It processes data between input and output
13.
What is the role of the input layer in a neural network?
a)
To calculate weights
b)
To receive data from the user
c)
To provide output
d)
To generate features
14.
What does the output layer in a neural network represent?
a)
Hidden patterns
b)
Data received from the user
c)
Final results of the network
d)
Intermediate processing steps
15.
What are weights in a neural network?
a)
Data inputs
b)
Numbers that represent layers
c)
Values that determine the importance of inputs
d)
Filters for inputs
16.
What do filters do in neural networks?
a)
Extract important features
b)
Store data
c)
Provide output directly
d)
Define network architecture
17.
What does sentiment analysis help detect?
a)
Word length
b)
Sentence structure
c)
Grammar mistakes
d)
Emotions like happiness or anger
18.
What is the goal of feature extraction in text processing?
a)
To make sentences longer
b)
To create new words
c)
To simplify sentences
d)
To identify key patterns or words
19.
Which is an example of a feature for text analysis?
a)
Font size
b)
Background color
c)
File type
d)
Word frequency
20.
Which of these emotions can sentiment analysis detect?
a)
Confusion
b)
Sadness
c)
Complexity
d)
Focus
21.
What is the role of the input layer in a neural network?
a)
To receive data from the user
b)
To calculate weights
c)
To provide output
d)
To generate features
22.
What does the output layer in a neural network represent?
a)
Hidden patterns
b)
Final results of the network
c)
Data received from the user
d)
Intermediate processing steps
23.
What do filters do in neural networks?
a)
Store data
b)
Provide output directly
c)
Define network architecture
d)
Extract important features
24.
Which is an example of a feature for text analysis?
a)
Font size
b)
Background color
c)
Word frequency
d)
File type
25.
How does deep learning help in translation?
a)
By detecting grammar errors
b)
By finding similar languages
c)
By understanding and converting sentence meanings
d)
By learning words directly
26.
What does the hidden layer in a neural network do?
a)
It provides input to the system
b)
It is visible to the user
c)
It stores the final output
d)
It processes data between input and output
27.
What does the output layer in a neural network represent?
a)
Final results of the network
b)
Hidden patterns
c)
Data received from the user
d)
Intermediate processing steps
28.
What are weights in a neural network?
a)
Data inputs
b)
Filters for inputs
c)
Numbers that represent layers
d)
Values that determine the importance of inputs
29.
What do filters do in neural networks?
a)
Store data
b)
Provide output directly
c)
Extract important features
d)
Define network architecture
30.
Which is an example of a feature for text analysis?
a)
Font size
b)
Word frequency
c)
Background color
d)
File type
31.
How does deep learning help in translation?
a)
By detecting grammar errors
b)
By finding similar languages
c)
By learning words directly
d)
By understanding and converting sentence meanings
32.
Which of these emotions can sentiment analysis detect?
a)
Confusion
b)
Complexity
c)
Focus
d)
Sadness
33.
What does sentiment analysis help detect?
a)
Word length
b)
Grammar mistakes
c)
Sentence structure
d)
Emotions like happiness or anger
34.
Which of these emotions can sentiment analysis detect?
a)
Confusion
b)
Complexity
c)
Sadness
d)
Focus
35.
What are weights in a neural network?
a)
Data inputs
b)
Numbers that represent layers
c)
Values that determine the importance of inputs
d)
Filters for inputs
36.

Label the weights received by all.

A
B
C
D
E
F
37.

Label the neurons connected to a11

A
B
C
D
E
F
G
H
38.

Label the sentiments that AI can detect

a)Neutral
b)Angry
c)Unhappy
d)Satisfied
e)Happy
1
2
3
4
5
1)
2)
3)
4)
5)
39.

How can AI help us learn which customers are unhappy? _________ ________

(a)  

40.

All words highlighted in red here, are called (a)   , which generally are non value adding. These words mostly do not help us in understanding sentiment behind a review. So, we would drop these.

41.

The highlighted (a)   depicts how the same dictionary word ‘recommend’ is used in different forms. These words have the message inside to detect sentiment by AI.

42.

Explain why feature extraction is important for ML? (research)

4 lines
43.

Computer imaging can be defined as the __________ and _______of visual information by computer.

a)

acquisition and processing

b)

editing nd processing

c)

acquisition and Manipulation

44.

Processed images are for use by a computer is ____

a)

Vision applications

b)

image processing applications.

45.

______________ involve the manipulation of image data for

viewing by people.

a)

Image processing application

b)

Vision applications

46.

which one of the list computer vision in Image Analysis, which involves

the examination of the image data for solving a vision problem.

a)

Edge Detection

b)

Segmentation

c)

Transformation

d)

All

e)

None

47.

________ is the process of taking an image with some

known or estimated degradation, and restoring it to its original

appearance.

a)

Image Edge Detection

b)

Image restoration

c)

Image Transformation

48.

_______involves taking an image and improving

it visually, typically by taking advantage of the human visual system’s response.

a)

Pattern (object) classification

b)

Feature extraction

c)

Image enhancement

49.

Images can be represented as an _____.

a)

array form

b)

matrix form

c)

vector.

50.

Which of the following is NOT a primary component of the sensor systems in autonomous vehicles?

a)

Cameras

b)

Radar

c)

Wi-Fi

d)

LiDAR

51.

Fill in the blank: Machine learning in autonomous vehicles helps in ______ decision-making processes.

a)

slowing

b)

improving

c)

ignoring

d)

complicating

52.

Fill in the blank: In autonomous vehicles, redundancy involves backup systems that maintain ______ if the main system fails.

a)

speed

b)

safety

c)

fuel

d)

data

53.

Fill in the blank: V2X communication allows vehicles to ______ with each other and their environment.

a)

communicate

b)

ignore

c)

avoid

d)

collide

54.

Fill in the blank: The six levels of automation describe the degrees of automation from ______ to full automation.

a)

partial

b)

no automation

c)

manual

d)

semi

55.

In autonomous vehicles, redundancy refers to:

a)

Extra data collected by the sensors

b)

Backup systems that maintain safety if the main system fails

c)

Additional passenger safety features

d)

Extra fuel supplies

56.

Which type of sensor technology allows an autonomous vehicle to create detailed 3D maps of its surroundings?

a)

Camera sensors

b)

Radar

c)

GPS

d)

LiDAR

57.

Artificial Intelligence (AI) in autonomous vehicles primarily helps the vehicle to:

a)

Make independent decisions based on sensor data

b)

Connect with other vehicles on the road

c)

Communicate with passengers in multiple languages

d)

Drive faster than a human-driven vehicle

58.

What does LiDAR stand for?

a)

Light Detection and Ranging

b)

Laser Imaging and Detection

c)

Light Image Data Analysis Range

d)

Light Identification Data Array

59.

Why do AI and ML need large volumes of data?

a)

To understand the environment.

b)

To train algorithms and improve accuracy.

c)

To emulate human abilities.

d)

To solve problems based on data.

60.

Purpose of machine learning models?

a)

Create human-like properties in machines.

b)

Develop algorithms to solve problems.

c)

Look for patterns in data and draw conclusions.

d)

Program computers explicitly.

61.

Main difference between AI and ML?

a)

AI trains machines for human tasks, while ML trains machines how to learn.

b)

AI and ML are the same.

c)

AI mimics human abilities, while ML solves problems based on data.

d)

I uses algorithms, while ML uses speech interfaces.

62.

What is the concept that a computer can mimic human abilities?

a)

Virtual Reality

b)

Machine Learning

c)

Artificial Intelligence

d)

Blockchain

63.

What is the method behind how machines learn from data?

a)

Data Analysis

b)

Predictive Modeling

c)

Algorithmic Processing

d)

Machine Learning

64.

Which of the following is a specific subset of AI that trains a machine how to learn?

a)

Deep Learning

b)

Neural Networks

c)

Machine Learning

d)

Natural Language Processing

65.

What is the science of training machines to perform human tasks?

a)

Virtual Reality

b)

Robotics

c)

Blockchain

d)

Artificial Intelligence

66.

What is the main purpose of edge detection in image segmentation?

a)

To smooth the image

b)

To find the boundaries of objects

c)

To increase the contrast

d)

To resize the image

67.

Which technology helps improve the accuracy of image segmentation in complex tasks like recognizing objects in photos?

a)

Neural Networks

b)

Photoshop

c)

3D Printing

d)

Bluetooth

68.

In thresholding, what is used to segment the image?

a)

Colour contrast

b)

A specific intensity value

c)

Object size

d)

The angle of the object

69.

In image segmentation, which method identifies boundaries between different objects?

a)

Edge detection

b)

Blurring

c)

Resizing

d)

Color balancing

70.

Which of the following is a common application of image segmentation?

a)

  • Creating 3D models from 2D images

b)

Detecting objects in self-driving cars

c)

  • Compressing images for storage

d)

Enhancing image brightness

71.

Which emerging technology is crucial for improving real-time image segmentation performance?

a)

Quantum computing

b)

Edge AI

c)

Blockchain

d)

3D printing

72.

In what industry is image segmentation commonly used for medical imaging?

a)

Agriculture

b)

  • Entertainment

c)

  • Healthcare

d)

Transportation

73.

Which of the following is the simplest form of image segmentation?

a)

Edge detection

b)

Thresholding

c)

Clustering

d)

Morphological operations

74.

What is image segmentation?

a)

Combining multiple images

b)

Dividing an image into meaningful parts

c)

Enhancing the contrast of an image

d)

Filtering noise from an image

75.

What is this an example of?

a)

Diagram

b)

Caption

c)

Illustration

d)

Title

76.

An author would use this diagram to

a)

Compare and contrast adult brain with a child's brain

b)

Identify the parts and areas within a human brain

c)

Explain how the Occipital lobe is the biggest part of the brain

d)

Show the reader where the brain is located within the human body

77.

The _____ identifies what the topic of an article or book will be about.

a)

Subheading

b)

Glossary

c)

Title

d)

Photograph

78.
A line that has dates in chronological order is a...?
a)
chart
b)
map
c)
timeline
d)
fact box
79.

This is an example of ____________ text feature? NOTICE THE LABELS added to the picture.

a)

Index

b)

Table of contents

c)

Glossary

d)

Diagram

80.

What text feature is this?

a)

Highlighted Font

b)

Heading

c)

Graph

d)

Caption

81.

What text feature is this?

a)

Heading

b)

Graphic Aid

c)

Glossary

d)

Bold text

82.

What purpose would this have in an article about tourism in Antarctica?

a)

It helps readers visualize the changes in tourist numbers from 1992 until 2008

b)

It helps tourists decide when to visit Antarctica

c)

It gives reasons not to visit Antarctica in the winter.

d)

It informs the reader of reasons to visit Antarctica.

83.

Under which heading might you find information on Will’s childhood chores?

a)

Hard Work at Home

b)

Early Fame

c)

Movie Magic

d)

How He Does It

84.

What is the purpose of these subheadings?

a)

To help the reader understand the author’s opinion

b)

To help the reader visualize the information

c)

To help the reader find the main ideas in each section

d)

To help the reader place events in order

85.

What text feature is used in the red boxes?

a)

Sidebar

b)

Column

c)

White Space

d)

Subheading

86.

The purpose of graphics (such as graphs, tables, pictures, or maps) is to

a)

Help the reader visualize important information

b)

Describe what is found in a photo or illustration

c)

Separate text into sections based on main ideas

d)

Show information that occurs in a certain order

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