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Introduction to Machine Learning

Total questions: 10

Worksheet time: 6mins

Name
Class
Date
1.

Machine learning is a subset of artificial intelligence

a)

True

b)

False

2.

 

Machine learning is one of the steps in a data science project.

a)

True

b)

False

3.

Which of the below is not supervised learning?

a)

Spam email identification

b)

House price prediction

c)

Clustering customers into different groups of similarity

4.

Which of the below is not unsupervised learning?

a)

Fraud detection

b)

Customer segmentation

c)

Face recognition

5.

In tabular data, what does a row and column represent?

a)

Row = feature, column = entity

b)

Column = feature, row = entity

6.

In which cases, machine learning is NOT useful?

a)

A bank wants to call to sell bond to top 10 percent customers

b)

A bank wants find potential customers to offer lending but has no data about past interaction

c)

A bank want to segment customers into different groups to serve them better

d)

A bank wants to display credit card banner to all digital app users

7.

Which is NOT a part of a data science project?

a)

Define business problem

b)

Scrap data that is needed

c)

Take care of customers to get their best feedbacks

d)

Train the model

e)

Generate leads of potential customers for business

8.

There are four components in a customer life cycle:

acquisition, centralisation, (a)   , engagement

9.

How many pillars are usually applied to design ML project lifecycle?

(a)  

10.

To predict which customers are more likely to purchase BANCA, a machine learning needs historical data of customers who:

a)

bought banca

b)

declined to buy banca

c)

both bought banca and who declined to buy banca

d)

all customers of TCB