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What is Explainable Artificial Intelligence?

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Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are essential for building trust, ensuring fairness, and addressing ethical concerns. Businesses can benefit from explainable AI by gaining insights into AI-driven predictions and making informed decisions based on those insights.

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…

Clustering

Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or…

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…

Hyperparameters

Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as…
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