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What is Uncertainty in Artificial Intelligence?

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Uncertainty in AI refers to the unpredictability or lack of full knowledge about a situation or outcome. AI models often encounter uncertainties due to incomplete or noisy data. Techniques such as Bayesian Inference and Probabilistic Graphical Models are used to quantify and manage uncertainty in AI.

Other Definitions

Feature Extraction

Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…

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…

Forecasting

Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make…

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…
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