Understanding Supervised and Unsupervised Learning in Machine Learning
Machine learning, a subset of artificial intelligence, is revolutionizing the way computers learn and make decisions. Two fundamental paradigms within machine learning are supervised learning and unsupervised learning. In this article, we will delve into the intricacies of these two approaches, exploring their principles, applications, and key differences. Supervised Learning : Supervised learning is a type of machine learning where the algorithm is trained on a labelled dataset. This means that the input data is paired with corresponding output labels, allowing the model to learn the relationship between the inputs and the desired outputs. Key Concepts : 1. Labelled Data : - The training dataset consists of input-output pairs, where each input is associated with a correct output label. 2. Training Process : - During training, the algorithm learns to map inputs to outputs by adjusting its parameters based on the pro...