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G9 Machine learning algorithm

Total questions: 27

Worksheet time: 16mins

Name
Class
Date
1.

Clasificacion es un…

a)

Unsupervised learning

b)

Reinforcement learning

c)

Supervised learning

d)

Ninguna de las anteriores

2.

Machine learning is a subset of artificial intelligence

a)

True

b)

False

3.

What is the relationship between model and algorithm?

a)

Algorithm + model = data

b)

Algorithm = Model + data

c)

Model = Algorithm(data)

d)

Data = Algorithm(model)

4.

Which of the following yields discrete categorical outputs?

a)

Anomaly detection

b)

Regression

c)

Classification

d)

Feature Learning

5.

The study of algorithms that enable the machine to learn from data. .

a)

Features

b)

Machines Learning

c)

AI

6.

Machine Learning is a subset of ………

a)

Features

b)

Machines Learning

c)

AI

7.

Machine learning algorithms are just like traditional programming.

a)

True

b)

False

8.

AI must use machine learning algorithms.

a)

True

b)

False

9.

AI is a small part of machine learning.

a)

True

b)

False

10.

AI is a small part of machine learning.

a)

True

b)

False

11.

What is machine learning?

a)

A way for computers to recognize patterns and make decisions without explicit programming

b)

A tool for internet searches only

c)

A type of artificial intelligence that is decades away

d)

A programming language

12.

What kind of data can machine learning process?

a)

Only numerical data

b)

Images, video, audio, or text

c)

Only audio and video

d)

Only text and images

13.

Type of Supervised machine learning :

a)

Regression

b)

Clustering

c)

Reinforcement

d)

Association

14.

_________ is an algorithms where AI component learns by the hit & trial method .

a)

Regression

b)

Clustering

c)

Reinforcement

d)

Association

15.

Which of the following is not type of learning?

a)

Semi-unsupervised Learning

b)

Unsupervised Learning

c)

Supervised Learning

d)

Reinforcement Learning

16.

This picture shows an application of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Clustering

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

17.
In computer science what does AI stand for?
a)
Artificial Instrument
b)
Artificial Intelligence
18.

Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

19.

This picture shows a result of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Regression

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

20.

This picture shows a result of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Regression

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

21.

__________________ algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.

a)

Artificial Intelligence

b)

Machine Learning

c)

Deep Learning

d)

Traditional Learning

22.

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

23.

What are the two types of Supervised Learning?

a)

Classification

b)

Declassification

c)

Progression

d)

Regression

24.

ML is a field of AI consisting of learning algorithms that?

a)

Improve their performance

b)

At executing some task

c)

Over time with experience

d)

All of the above

25.

Labeled Data are used in _______ Machine Learning algorithm

a)

Supervised

b)

Unsupervised

26.

Labeled Data are used in _______ Machine Learning algorithm

a)

Supervised

b)

Unsupervised

27.

Unlabeled Data are used in _______ Machine Learning algorithm

a)

Supervised

b)

Unsupervised