TRAINING ON ARTIFICIAL INTELLIGENCE FOR STUDENTS: e-Compendium, Machine Learning: Concepts and Applications

Abstract

Machine learning (ML) techniques which usually resort to soft computing are mostly data-driven in the sense that they are very much complementary to the model-driven techniques like regression or time series models. They are also called data mining techniques owing to their very nature of mining and revealing any hidden information present in the data with a large number of variables and data points involved and are very much computer-intensive. In contrast to traditional methods, using ML techniques, the very large database is allowed to bring out non-linear complex relationships that may exist between the variables involved which otherwise cannot be captured by the former.