Machine learning gives computer systems an ability to learn without explicit programming. One of the most common types of machine learning is supervised learning. Supervised learning consists of a set of different algorithms which formulates a learning problem and solves them by mapping inputs and outputs using historical data. The algorithms analyze the input and a corresponding output, then link them together to find a relationship (learning). Finally, for the new given dataset, it will predict the output by using this learning.
In order to differentiate between supervised and unsupervised learning, we can think about input/output-based modeling. In supervised learning, the computer system will be supervised with labels for every set of input data. In unsupervised learning, the computer system will only use input data without any labels...
