AI Glossary - AI & Machine Learning Terms Dictionary

AI Glossary provides comprehensive definitions of artificial intelligence and related terms.

Understanding AI terminology is essential for engaging with AI research, reading papers, following discussions, and participating in the AI community. This glossary provides clear, concise definitions of important AI terms, organized alphabetically for easy reference.

Terms are explained in accessible language with context and examples where helpful. This glossary covers fundamental AI concepts, machine learning terms, deep learning terminology, neural network definitions, optimization terms, evaluation metrics, research methods, and specialized terminology.

Epoch: One complete pass through the entire training dataset during model training.

Evaluation Metric: A measure used to assess model performance, such as accuracy, precision, recall, or F1-score.

Explainable AI (XAI): AI systems that provide explanations for their decisions, improving transparency and trust.

Learning Rate: A hyperparameter controlling the step size in optimization algorithms.

Loss Function: A function measuring the difference between model predictions and true values, minimized during training.

Label: The correct answer or category for training examples in supervised learning.

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