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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

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…

Object Recognition

Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…

Dimensionality Reduction

Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant…

Generative Adversarial Networks (GANs)

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used…
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