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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

Probabilistic Graphical Models

Probabilistic Graphical Models is a type of statistical model used in Machine Learning and Artificial Intelligence. They represent complex relationships between variables through graphs…

Feature Extraction

Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…

Synthetic Data

Synthetic Data is artificially generated data that mimics real-world data. Synthetic data can be used to train Machine Learning models when real data is…

Federated Learning

Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…
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