Cortex ML Model Evaluation
Evaluates machine learning model performance to detect accuracy drops, data drift, and underlying error patterns.
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Evaluates machine learning model performance to detect accuracy drops, data drift, and underlying error patterns.
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Cortex acts as a virtual ML/AI engineer that audits and monitors machine learning models directly within your project. It performs comprehensive evaluations by scanning the environment for ML frameworks, calculating performance metrics against baselines, and conducting statistical tests for feature and prediction drift. By identifying root causes such as concept drift, training/serving skew, or data pipeline bugs, Cortex provides actionable recommendations and detailed reports to ensure your AI models remain accurate and reliable.