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Concepts of Machine Learning

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

Which ML algorithm is being used to perform classification in this image?

a)

Naive Bayes

b)

SVM

c)

AVM

d)

Decision Tree

2.

Which of the following is NOT a good way to define AI

a)

AI is Augmented Intelligence and is not intended to replace human intelligence rather extend human capabilities

b)

AI is the application of computing to solve problems in an intelligent way using algorithms.

c)

AI is the use of algorithms that enable computers to find patterns without humans having to hard code them manually

d)

AI is all about machines replacing human intelligence.

3.

........... are more commonly used to find insights into nearly everything from marketing to law enforcement.

a)

Data mining

b)

Big data

c)

Predictive analytics

d)

Machine learning

4.

.......... measures the set of possible good recommendations your system comes up with.

a)

Recall

b)

Precision

c)

Data

d)

Accuracy

5.

The task "Future stock prices or currency exchange rates" falls under which category?

a)

Recognizing Anomalies

b)

Prediction

c)

Generating Patterns

d)

Recognition Patterns

6.

How many new opportunities and job roles does the World Economic Forum expect that AI will create in the next few years?

a)

165 million

b)

7 million

c)

133 million

d)

48 million

7.

Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?

a)

Classifying emails as spam or not spam

b)

Watching you label emails as spam or not spam

c)

The number of emails correctly classified as spam/not spam

d)

None of the above

8.

........ measures how accurate the system’s recommendation was.

a)

Precision

b)

Recall

c)

Model

d)

Data

9.

A .......... is a mathematical representation of an object or a process.

a)

Method

b)

Object

c)

Data

d)

Model

10.

The Number of coefficients required to estimate a simple linear regression?

( Hint: think of a simple linear regression equation)

a)

1

b)

2

c)

0

d)

3

11.

KNN is ___________ algorithm

a)

Eager Learner

b)

Lazy Learner

12.

Estimating the price of a house is a problem solved through.....

a)

Cluster

b)

Class

c)

Regression

13.

Which of these is NOT a current application of AI?

a)

Self-Driving vehicles utilizing Computer Vision to navigate around objects

b)

Collaborative Robots helping humans lift heavy containers

c)

Classifying rock samples to identify best places to drill for oil

d)

Making precise patient diagnosis and prescribing independent treatment

14.

......... has its own challenging properties that include volume, velocity, and variety.

a)

Data mining

b)

Machine learning

c)

Big data

d)

Statistics

15.

If your algorithm gives very good accuracy for training set , but bad accuracy for test set, it is.......

a)

Underfitting

b)

Best fit

c)

Overfitting

d)

No Fit

16.

Which of these statements is true?

a)

AI is the subset of Data Science that uses Deep Learning algorithms on structured big data

b)

Data Science is a subset of AI that uses machine learning algorithms to extract meaning and draw inferences from data

c)

Artificial Intelligence and Machine Learning refer to the same thing since both the terms are often used interchangeably

d)

Deep Learning is a specialized subset of Machine Learning that uses layered neural networks to simulate human decision-making

17.

What is a significant way in which developers of AI systems can guard against introducing bias?

a)

Using only examples from their own environment as training data.

b)

Using government approved algorithms.

c)

Providing effective training data and performing regular tests and audits.

d)

Using less varied AI systems and datasets.

18.

........... and predictive analytics are bringing equally big changes to academia, the job market, and virtually every competitive company out there.

a)

Big data

b)

Models

c)

Clustering

d)

Data

19.

Natural Language AI algorithms that learn by example are the reason we can talk to machines and they can talk back to us.

a)

True

b)

False

c)

Can't Say

d)

Neither True nor False

20.

AI is the fusion of many fields of study. Which of these fields, along with Computer Science, plays a role in the application of AI?

a)

Statistics

b)

Philosophy

c)

Mathematics

d)

All responses are correct

21.

What type of Machine Learning Algorithm is suitable for predicting the continuous dependent variable?

a)

Logistic Regression

b)

Linear Regression

c)

Decision Tree Classifier

d)

KNN Classifier

22.

Field of study that gives computers the ability to learn without being explicitly programmed.

a)

Deep Learning

b)

Machine Learning

c)

Data Science

23.

What would make a robot intelligent?

a)

It responds to the environment.

b)

It responds to the environment according to previous experiences.

c)

It calculates mathematical problems faster than human minds.

d)

It can jump 1.5 meters higher than humans.

24.

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

a)

Recognizing Anomalies

b)

Prediction

c)

Generating Patterns

d)

Recognition Patterns

25.

A major benefit of an machine with AI is

a)

it could do a job too dangerous for a human

b)

it could love you like a brother

c)

it could chop up your vegetables