Differences between Supervised and Unsupervised Machine Learning
Machine Learning is one of the most trending technologies in the field of artificial intelligence. It involves the use of algorithms that allow machines to learn by imitating the way humans learn. There are two main types of Machine Learning, the supervised Machine Learning and the unsupervised Machine Learning. Let us look at the differences between these two large groups, their features and what they are used for.
Supervised machine learning
This type of Machine Learning uses algorithms that "learn" from the data entered by a person. In supervised machine learning;
The algorithm generates expected output data, since the input has been labeled and classified by someone.
Human intervention is needed to label, classify and enter the data in the algorithm.
There are two types of data that can be introduced in the algorithm:
Classification: classify an object within different classes. For instance, to determine if a patient is sick or if an email is spam.
Regression: predict a numerical value. It would be the case of the prices of a house when choosing different options or the demand of occupation of a hotel.
Some practical applications of this type of Ma