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This article explores various explainable AI (XAI) techniques, such as Local Interpretable Model-agnostic Explanations (LIME), which aim to make the predictions of complex machine learning models understandable to humans. These techniques can be categorized into model-agnostic and model-specific methods, each suited for different types of AI models and applications.
