The machine learning algorithms are broadly classified into 3 categories.
Machine learning is a vast field comprising of various data related operations such as analysis, prediction, decision making and much more. These applications require a set of well-defined steps to proceed with the idea designed for model construction. A set of well-defined instructions that produces some output or accomplishes a particular task is called an algorithm. The machine learning algorithms are broadly classified into 3 categories – Supervised, Unsupervised and Reinforcement Learning.
To choose an appropriate algorithm in machine learning, identifying the kind of problem is very necessary as each of these algorithms obeys a different plan of attack to deal with the proposed problem. Supervised learning uses an approach where the output is already known to the user or the individual while unsupervised learning concentrates on the concept of similarity in properties of the objects. Reinforcement learning differs from both of them and uses the art of learning from experiences.
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