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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

Cognitive Computing

Cognitive Computing involves creating computer systems that can imitate human cognitive abilities, such as perception, reasoning, learning, and problem-solving. By combining AI, Machine Learning,…

Data Preprocessing

Data Preprocessing involves preparing and cleaning raw data before analysis. By removing noise, selecting relevant features, and addressing missing values, businesses can ensure data…

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…

Transfer Learning

Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models…
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