Introduction to Machine Learning

Machine learning is ___ field

• Inter-disciplinary

• Single

• Multi-disciplinary

• All of the Above

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.

• Training

• Experience

• Database

• Algorithm

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

• Machine Learning

• Data mining

• Neural Networks

• Robotics

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 _____.

• Hypothesis

• Inductive hypothesis

• Learning

• Concept learning

Factors which affect performance of a learner system does not include

• Representation scheme used

• Training scenario

• Type of feedback

• Good data structures

Different learning methods does not include

• Memorization

• Analogy

• Deduction

• Introduction

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

• Language units

• Role structure of units

• System constraints

• Structural units

How many types are available in machine learning?

• 1

• 2

• 3

• 4

The k-means algorithm is a

• Supervised learning algorithm

• Unsupervised learning algorithm

• Semi-supervised learning algorithm

• Weakly supervised learning algorithm

The Q-learning algorithm is a

• Supervised learning algorithm

• Unsupervised learning algorithm

• Semi-supervised learning algorithm

• Reinforcement learning algorithm