Supervised Learning: What It's, Why Significant , How it Works, Types, Uses, Advantages, Disadvantages and Strategies ! Step Into the Era of Artificial Intelligence and Embrace Innovation !!
Abstract: Supervised machine learning is the construction of algorithms that are able to produce general patterns and hypotheses by using externally supplied instances to predict the fate of future instances. Supervised machine learning classification algorithms aim at categorizing data from prior information. Classification is carried out very frequently in data science problems. Various successful techniques have been proposed to solve such problems viz. Rule-based techniques, Logic-based techniques, Instance-based techniques, stochastic techniques. Supervised learning is a broadly used machine learning methodology with its applications in diverse areas like Natural Language Processing, image and video classification, medical analysis, and many other prevailing fields. This chapter explains briefly about various supervised machine learning techniques, applications and strategies for awesome results. Keywords Supervised Learning , Rule-based techniques, Logic-based techniq