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Introduction to artificial intelligence and machine learning

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

What does AI stand for?

a)

Artificial instrument

b)

Artificial intelligence

c)

Augmented intelligence

d)

Artificial intellectual

2.

Artificial Intelligence is the process that allows computers to learn and make decisions like humans

a)

True

b)

False

3.

What would make a robot intelligent?

a)

It calculates mathematical problems faster than human minds.

b)

It responds to the environment.

c)

It responds to the environment according to previous experiences.

d)

It can jump 1.5 meters higher than humans.

4.

A major benefit of an machine with AI is

a)

it could do a job too dangerous for a human

b)

it could chop up your vegetables

c)

it could love you like a brother

d)

it could help you to hack someone phone

5.

What kind of learning algorithm for "Future stock prices or currency exchange rates"?

a)

Recognition Patterns

b)

Recognizing Anomalies

c)

Generating Patterns

d)

Prediction

6.

What kind of learning algorithm for "Facial identities or facial expressions"?

a)

Generating Patterns

b)

Recognizing Anomalies

c)

Recognition Patterns

d)

Prediction

7.

Which of the following is not type of learning?

a)

unsupervised learning

b)

semi-unsupervised learning

c)

supervised learning

d)

reinforcement leanrning

8.

Estimate the price of a house

a)

Cluster

b)

Classification

c)

Regression

9.

Identifying a man

a)

Cluster

b)

Classification

c)

Regression

10.

Students grade vs attendance

a)

Cluster

b)

Classification

c)

Regression

11.

Text Recognition

a)

Cluster

b)

Classification

c)

Regression

12.

Group different cats based on their looks

a)

Cluster

b)

Classification

c)

Regression

13.

 

Identify coins

a)

Cluster

b)

Classification

c)

Regression

14.

Identify the Problem:

We have Information of all previous general elections with respect to party, votes, candidates, locality, issues in nation, etc. With All this information we need to find the winner of next general election.

a)

Classification

b)

Regression

c)

Clustering

d)

None of them

15.

Machine learning for classification, EXCEPT

a)

K-means

b)

KNN

c)

ANN

d)

SVM

16.

These are performance evaluation for classification, EXCEPT

a)

Accuracy

b)

Specificity

c)

Error rate

d)

Mean squared error

17.

Machine learning process, includes

a)

filtering

b)

data collection

c)

model training

d)

model evaluation

e)

ALL

18.

What device below is not an example of Machine Learning?

a)

Wearable fitness tracker

b)

Speech to text

c)

Google search

d)

None

19.

NOT AI programming

a)

C programming

b)

Python

c)

Java

d)

Assembly language

20.

Not AI platform

a)

IBM Watson

b)

Visual Basic

c)

Google Colab

d)

Tensorflow

21.

In this type of Machine Learning, an AI system is presented with unlabeled, uncategorized data and the system’s algorithms act on the data without prior training. The output is dependent upon the coded algorithms.

a)

Supervised learning

b)

Unsupervised learning

c)

Reinforcement learning

d)

Technique learning

22.

ANN is ......

a)

a system that have capabilities to address many different tasks

b)

a system requires many training compared to biological system

c)

the memory is followed a pattern of distributed representation

d)

a system that capable to learn with one training presentation

23.

McCulloch and Pitts proposed the first computational model of neuron

a)

2014

b)

1958

c)

1969

d)

1943

24.

In ANN training process

a)

Data validation must more than data training

b)

'1' can be set as initial weights

c)

Mean squared error can perform as model evaluation

d)

Target is not required

25.

A training able to classify subjects correctly, result easy to interpret and prediction rate is acceptable.

a)

Good model

b)

Underfitting model

c)

Overfitting model