Artificial Intelligence

Supervised Learning: Understanding the Basics and Applications What is Supervised Learning ? Supervised learning is a popular technique in machine learning that involves training algorithms to predict outputs based on input data. It is called “supervised” because the algorithm is given labeled examples, which it uses to learn the relationship between inputs and outputs. The goal is to develop a model that can accurately predict outputs for new, unseen inputs. In this blog post, we’ll cover the basics of supervised learning, including key concepts, types of algorithms, how it works, and real-world applications. Concepts in Supervised Learning: In supervised learning, the algorithm is given a set of input-output pairs, called the training data. The inputs are typically represented as features, and the outputs are the labels. The algorithm uses this training data to learn a mapping function that takes inputs to outputs. This function can then be used to make predic