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What is Supervised Learning?

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Supervised Learning is a Machine Learning approach where models are trained using labelled data, with both input and output pairs. By learning from the provided examples, supervised learning algorithms can make predictions or classifications on new, unseen data. It is widely used in tasks like spam detection, sentiment analysis, and image recognition.

Other Definitions

Unsupervised Learning

Unsupervised Learning is a Machine Learning technique where models learn patterns and structures within data without labelled examples. By uncovering hidden relationships and clustering…

Support Vector Machines

Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…

Graph Neural Networks

Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform…

Zero-Shot Learning

Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved…
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