What's Supervised Learning? What's are Essential Topics in Supervised Learning to Become an Artificial Intelligence Expert? Explore More Possibilities from Emerging Perspectives!
Abstract: Supervised Learning is the process of teaching a model by feeding it input data as well as correct output data. This input/output pair is usually referred to as "labeled data." Think of a teacher who, knowing the correct answer, will either reward marks to or take marks from a student based on the correctness of her response to a question. This blog article includes about supervised learning, types, applications, advantages, disadvantages etc with modern approaches utilised under Supervised Learning Keywords : Supervised Learning, Models, advantages, disadvantages, emerging What is Supervised Learning? In machine learning and artificial intelligence, supervised learning refers to a class of systems and algorithms that determine a predictive model using data points with known outcomes. The model is learned by training through an appropriate learning algorithm (such as linear regression, random forests, or neural networks) that typically works through