Machine Learning: 3 Kinds of Algorithms

Machine learning algorithms is one of the hot topic in today’ s world. We are started our journey from Mainframe computers to PC and now in CLOUD computing. What is machine learning?

The definition says: Machine learning is a sub field of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a “Field of study that gives computers the ability to learn without being explicitly programmed”

Machine Learning Jobs
Machine Learning Jobs

Related: Commonly Used Languages in Machine Learning

Three kinds of machine learning algorithms:

Supervised learning: This algorithm consist of a target / outcome variable (or dependent variable) which is to be predicted from a given set of predictors (independent variables).

Un-supervised learning: In this algorithm, we do not have any target or outcome variable to predict / estimate.  It is used for clustering population in different groups

Reinforcement learning: Using this algorithm, the machine is trained to make specific decisions. It works this way: the machine is exposed to an environment where it trains itself continually using trial and error.

Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.