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Introduction to Machine Learning

Total questions: 12

Worksheet time: 12mins

Name
Class
Date
1.

Machine learning is ___ field

a)

Inter-disciplinary

b)

Single

c)

Multi-disciplinary

d)

All of the Above

2.

A computer program is said to learn from __________ E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with E.

a)

Training

b)

Experience

c)

Database

d)

Algorithm

3.

__________ has been used to train vehicles to steer correctly and autonomously on road.

a)

Machine Learning

b)

Data mining

c)

Neural Networks

d)

Robotics

4.

Any hypothesis find an approximation of the target function over a sufficiently large set of training examples will also approximate the target function well over other unobserved examples. This is called _____.

a)

Hypothesis

b)

Inductive hypothesis

c)

Learning

d)

Concept learning

5.

Factors which affect performance of a learner system does not include

a)

Representation scheme used

b)

Training scenario

c)

Type of feedback

d)

Good data structures

6.

Different learning methods does not include

a)

Memorization

b)

Analogy

c)

Deduction

d)

Introduction

7.

A model of language consists of the categories which does not include

a)

Language units

b)

Role structure of units

c)

System constraints

d)

Structural units

8.

How many types are available in machine learning?

a)

1

b)

2

c)

3

d)

4

9.

The k-means algorithm is a

a)

Supervised learning algorithm

b)

Unsupervised learning algorithm

c)

Semi-supervised learning algorithm

d)

Weakly supervised learning algorithm

10.

The Q-learning algorithm is a

a)

Supervised learning algorithm

b)

Unsupervised learning algorithm

c)

Semi-supervised learning algorithm

d)

Reinforcement learning algorithm

11.

This type of learning to be used when there is no idea about the class or label of a particular data

a)

Supervised learning algorithm

b)

Unsupervised learning algorithm

c)

Semi-supervised learning algorithm

d)

Reinforcement learning algorithm

12.

The model learns and updates itself through reward/punishment in case of

a)

Supervised learning algorithm

b)

Unsupervised learning algorithm

c)

Semi-supervised learning algorithm

d)

Reinforcement learning algorithm