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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

Large Language Model (LLM)

A Large Language Model refers to a type of advanced Artificial Intelligence model designed to exhibit human-like language understanding and generation abilities. LLMs are…

Explainable Artificial Intelligence

Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are…

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…

Bayesian Networks

Bayesian networks are Probabilistic Graphical Models that represent and evaluate uncertainty and conditional dependencies between variables. Industries such as healthcare and finance use Bayesian…
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