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What is Feature Extraction?

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Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting key information, businesses can improve efficiency, reduce noise, and focus on crucial variables for analysis.

Other Definitions

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…

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…

Algorithm

An algorithm is a set of rules and instructions that guide AI systems in solving problems or making decisions. Algorithms process data, analyse patterns,…

Reinforcement Learning

Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…
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