Machine Learning Paradigms: Supervised & Unsupervised Learning
Machine Learning has 2 primary paradigms: Supervised & Unsupervised Learning. Supervised models predict outcomes from labeled data, while Unsupervised models identify patterns in unlabeled data.
Machine Learning (ML) has become a cornerstone of technological advancements, driving innovations across industries. At its core, ML can be categorized into two primary paradigms: Supervised Learning and Unsupervised Learning. Supervised Learning: Training with Labels Supervised learning models are trained on labeled datasets, where the input data is paired with corresponding output labels. This approach enables the model to learn the relationship between inputs and outputs, making it a powerful tool for prediction and classification. 1. Regression Models: Predicting Contin...