Defining basic and necessary terminology of machine learning

This is an introductory lesson that presents the basic concepts related to machine
learning. It can be roughly divided into four sections.

The first section discusses the definition of machine learning. The second section describes the distinctions between different data categories, such as
independent vs. dependent variables, continuous vs. categorical data, and
training vs. testing data.

This section also briefly mentions the topic of Big Data.

The third section presents the concepts of supervised, unsupervised and reinforcement
learning, their applications, and the key differences between them. The lesson
is concluded with a section that presents the main types of machine learning
algorithms, such as support vector machines, random forests or neural networks,
and their most common applications.