Anomaly Detection
The process of identifying unusual patterns or outliers in data that do not conform to expected behavior.
The process of identifying unusual patterns or outliers in data that do not conform to expected behavior.
The process of anticipating, detecting, and resolving errors in software or systems to ensure smooth operation.
A software development practice where code changes are frequently integrated into a shared repository, with each change being verified by automated tests.
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes.
An environment used for testing software to identify issues and ensure quality before production deployment.
The use of software tools to run tests on code automatically, ensuring functionality and identifying defects without manual intervention.
A bias that occurs when the sample chosen for a study or survey is not representative of the population being studied, affecting the validity of the results.
A testing method that examines the code, documentation, and requirements without executing the program.