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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

Incremental Learning

Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…

Variational Autoencoders (VAE)

Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new…

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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