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AI vs ML vs DL

Total questions: 62

Worksheet time: 29mins

Name
Class
Date
1.

Which of the following best describes Artificial Intelligence (AI)?

a)

A branch of biology studying neural systems

b)

The simulation of human intelligence in machines

c)

A data storage technique

d)

A type of search algorithm

2.

Which of the following correctly represents the hierarchy among the fields?

a)

Deep Learning → Data Science → Artificial Intelligence → Machine Learning

b)

Data Science → Artificial Intelligence → Machine Learning → Deep Learning

c)

Artificial Intelligence → Machine Learning → Deep Learning → Data Science

d)

Machine Learning → Deep Learning → Artificial Intelligence → Data Science

3.

Which of the following is not a type of Artificial Intelligence?

a)

Narrow AI

b)

General AI

c)

Strong AI

d)

Data Analysis

4.

Machine Learning focuses primarily on:

a)

Predefined rules

b)

Learning patterns from data automatically

c)

Manual programming of every decision

d)

Symbolic reasoning only

5.

The first mathematical model of neural networks was introduced in:

a)

1950 by Alan Turing

b)

1943 by McCulloch and Pitts

c)

1980 by Geoffrey Hinton

d)

1965 by John McCarthy

6.

Which of the following correctly matches the type of learning with its description?

a)

Supervised Learning – Uses labeled data

b)

Unsupervised Learning – Uses unlabeled data

c)

Reinforcement Learning – Learns through rewards and penalties

d)

All of the above

7.

Deep Learning primarily differs from Machine Learning because:

a)

It uses multi-layered neural networks

b)

It requires less data

c)

It avoids mathematical computation

d)

It uses no neural network at all

8.

Convolutional Neural Networks (CNNs) are mainly used for:

a)

Image and voice recognition

b)

Sequential text processing

c)

Predictive time series analysis

d)

Symbolic logic reasoning

9.

Recurrent Neural Networks (RNNs) are best suited for:

a)

Random numeric data

b)

Structured tabular data

c)

Sequential or time-dependent data

d)

Static images

10.

Which of the following statements is true about Data Science?

a)

It excludes Artificial Intelligence techniques

b)

It is a subset of Machine Learning

c)

It encompasses AI, ML, and DL

11.

Which term refers to the simulation of human intelligence by machines?

a)

Artificial Intelligence

b)

Machine Learning with advanced visualization

c)

Deep Learning focused on data extraction

d)

Data Science using only statistics

12.

Who proposed the idea of whether machines could think like humans, inspiring the study of Artificial Intelligence?

a)

Alan Turing

b)

Isaac Newton with his laws of motion

c)

Charles Babbage with his analytical engine

d)

Ada Lovelace with her programming notes

13.

Narrow AI, General AI, and Strong AI are the three main types of which field?

a)

Artificial Intelligence

b)

Machine Learning focused on images

c)

Deep Learning for neural networks

d)

Data Science for information extraction

14.

Machine Learning is a subset of which broader field?

a)

Artificial Intelligence

b)

Data Science with programming

c)

Deep Learning for neural networks

d)

Statistical Analysis

15.

Deep Learning is a subset of which field?

a)

Machine Learning

b)

Artificial Intelligence focused on reasoning

c)

Data Science with domain knowledge

d)

Neural Networks

16.

The earliest mathematical model of a neural network was developed by McCulloch and Pitts in which year?

a)

1943

b)

1960s with the rise of computers

c)

1980s during the AI boom

d)

2000s with deep learning

17.

In which type of learning are models trained using labeled datasets?

a)

Supervised learning

b)

Unsupervised learning with hidden patterns

c)

Reinforcement learning using rewards

d)

Sequential learning for text data

18.

In which type of learning do models find hidden patterns in unlabeled data?

a)

Unsupervised learning

b)

Supervised learning with labels

c)

Reinforcement learning with feedback

d)

Deep learning for images

19.

In which type of learning does an agent learn through feedback, rewards, or penalties?

a)

Reinforcement learning

b)

Supervised learning with labeled data

c)

Unsupervised learning with patterns

d)

Sequential learning for speech

20.

Deep Learning uses interconnected layers of nodes called what?

a)

Neural Networks

b)

Data Layers for analysis

c)

Sequential Nodes for speech

d)

Image Layers for CNNs

21.

A neural network with more than three layers is called what kind of neural network?

a)

Deep neural network

b)

Sequential neural network for text

c)

Image neural network for CNNs

d)

Layered neural network for data

22.

The three main types of neural networks in deep learning are ANN, CNN, and which other type?

a)

RNN (Recurrent Neural Network)

b)

DNN (Deep Neural Network)

c)

SNN (Sequential Neural Network)

d)

INN (Image Neural Network)

23.

CNNs are primarily designed to process which type of data?

a)

Image or spatial data

b)

Sequential data such as text

c)

Numerical data for statistics

d)

Labeled data for supervised learning

24.

RNNs are especially effective for which type of data such as text or speech?

a)

Sequential data

b)

Image data for CNNs

c)

Numerical data for analysis

d)

Layered data for deep learning

25.

Machine Learning algorithms aim to improve automatically through what?

a)

Experience or data

b)

Programming with domain knowledge

c)

Statistical analysis only

d)

Visualization techniques

26.

Artificial Intelligence systems aim to mimic human abilities such as reasoning, problem-solving, and what else?

a)

Decision-making

b)

Data extraction from statistics

c)

Image recognition for CNNs

d)

Speech processing for RNNs

27.

Deep Learning became popular in the 21st century due to advancements by companies like which one and Google?

a)

Facebook

b)

Microsoft with cloud computing

c)

Apple with mobile devices

d)

IBM with Watson

28.

Data Science combines statistical analysis, programming, and domain knowledge to extract what from data?

a)

Insights or meaningful information

b)

Labeled datasets for supervised learning

c)

Hidden patterns for unsupervised learning

d)

Layers for neural networks

29.

The term Data Science was first coined in which year?

a)

1956s

b)

1940s with neural networks

c)

1980s with AI research

d)

2000s with big data

30.

What is the correct hierarchical order: Data Science → Artificial Intelligence → Machine Learning → what?

a)

Deep Learning

b)

Neural Networks for data

c)

Supervised Learning for labels

d)

Sequential Learning for speech

31.

Artificial Intelligence is superset of ________________________ & ________________________ ,

a)

Machine Learning & Neural Networks

b)

Machine Learning & Deep Learning

c)

Deep Learning & Neural Networks

32.

AI is a field of computer science aimed at developing machines which are intelligent enough to do certain tasks that would normally be performed only by (a)  

33.

___________________ is set of algorithms that allows computers to learn from data without being explicitly programmed.

a)

Machine Learning

b)

Deep Learning

c)

Neural Networks

34.

This requires computer scientists to formulate general-purpose learning algorithms that help machines learn more than just one task.

a)

Machine Learning

b)

Deep Learning

c)

Neural Networks

35.

Machine Learning is a subset of AI. ML deals with developing systems which can improve their performance with _________________.

a)

Experience

b)

Deep Learning

c)

Neural Networks

36.

Most of people are familiar with ______________learning from shopping on the Internet and being offered products related to their purchase.

a)

Machine

b)

Deep

37.

Machine learning is a subset of artificial intelligence

a)

True

b)

False

38.

Identify parametric machine learning algorithms

a)

Linear regression

b)

CNN

c)

Logistic regression

d)

Naïve Bayes

39.

Which of these statements is true about classical ML vs. deep learning?

a)

All deep learning algorithms are machine learning algorithms

b)

All machine learning algorithms are deep learning algorithms

c)

Classical ML is a subcategory of deep learning algorithms,based on neural networks

40.

What is the role of algorithms in Machine Learning?

a)

Algorithms are not used in Machine Learning

b)

Algorithms are used to predict the weather

c)

Algorithms are used to train the model, enabling it to learn from data and make predictions.

d)

Algorithms are used to clean the model

41.

How is Deep Learning used in AI?

a)

Deep Learning is used for predicting the weather

b)

Deep Learning is used for designing buildings

c)

Deep Learning is used for cooking recipes

d)

Deep Learning is used for tasks such as image and speech recognition, natural language processing, and decision making.

42.

The ability of a computer to understand images and videos

a)

Robotics

b)

Natural Language Processing

c)

Computer Vision

43.

The ability of a computer to understand human language is called

a)

NLP

b)

Computer Vision

c)

Medical Science

44.

Human face recognition is considered as

a)

NLP

b)

Computer Vision

45.

Objects tracking is considered as

a)

NLP

b)

Computer vision

46.

Voice to text is considered as

a)

NLP

b)

Computer Vision

47.

A machine that is specialized in one task or area.

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

48.

Intelligent machines that can learn any tasks that humans can do.

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

49.

A theoretical type of AI where the machine can outperform human intelligence in every task

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

50.

learning from examples in a training data set is a

a)

Supervised Learning

b)

Unsupervised Learning

51.

When the machine will be provided with features only. It will then try to group objects with similar features

a)

Supervised Learning

b)

Unsupervised Learning

52.

The machine will group objects with similar features but will not be able to identify what this group label

a)

Supervised Learning

b)

Unsupervised Learning

53.

If the computer is trained to recognize cars, bikes and trucks with a human supervision.

a)

Supervised Learning

b)

Unsupervised Learning

54.

Predict the price of a house

a)

Supervised Learning

b)

Unsupervised Learning

55.

Recommend a product based on your buying history

a)

Supervised Learning

b)

Unsupervised Learning

56.

What type of AI is here today and can recognize patterns?

a)

True Artificial Intelligence

b)

Machine Learning

c)

Alexa

d)

Allen Institute for Artificial Intelligence

57.

What kind of data can machine learning take in?

a)

Images, video, audio, or text

b)

Only images

c)

Only video

d)

Only audio

58.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Machine Learning

c)

Modern Programming

d)

Traditional Learning

59.

Which of the following is not type of learning?

a)

Semi-unsupervised Learning

b)

Unsupervised Learning

c)

Supervised Learning

d)

Reinforcement Learning

60.

What are the three types of Machine Learning? Choose three.

a)

Supervised Learning

b)

Learning Differentiated

c)

Unsupervised Learning

d)

Reinforcement Learning

e)

Technical Learning

61.

Labeled Data are used in _______ Machine Learning algorithm

a)

Supervised

b)

Unsupervised

62.

Unlabeled Data are used in _______ Machine Learning algorithm

a)

Supervised

b)

Unsupervised