Kinds of machine learning techniques
In the previous section, we saw an introduction to machine learning and an example modeling of a digit image. Now, we will see the different styles of machine learning techniques.
Supervised learning
In supervised learning, we are given a dataset of both the inputs and required outputs for the model; our goal is to create a model that will take any previously unseen data and output values that are true to the actual as much as possible. There are two kinds of supervised learning.
Classification
This is the term for cases when the output of the model is categorical. For example, in the case of digit classification, the output is one of the 10 different digits.
Regression
This is the term for cases when the output has continuous values, for example, a line fitting model. In it, the goal is to approximate the curve as much as possible so that the output of the model would be a value within a certain range.
Unsupervised learning
In this type of machine learning,...
