How does machine learning work?

But not all processes follow clear, unchanging rules, and most decisions in the real world do not lead to a single unambiguous answer. Machine Learning systems are probabilistic: tasks are executed and decisions are made on incomplete information and outcomes are assigned probabilities of being correct. Machine learning is suited to problems involving classification (dividing objects into two or more classes), regression (discovering relationships between variables) and clustering (grouping objects by similar characteristics).