Image recognition uses algorithms and models to interpret the visual world, converting images into symbolic information for use in various applications.

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Algorithmic bias results in unfair outcomes due to skewed or limited input data, unfair algorithms, or exclusionary practices during AI development.

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Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

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Synthetic data is artificially generated data that mimics the characteristics of real-world data without containing any actual information.

In the machine learning universe, unlabeled data is primarily used in unsupervised learning models.

Labeled data is raw data that has been assigned labels to add context or meaning, which is used to train machine learning models in supervised learning.