AI Modeling, Continuous Learning and Data Drift

Concept Drift vs Data Drift: How AI Can Beat the Change

Viso.ai

APRIL 4, 2024

Two of the most important concepts underlying this area of study are concept drift vs data drift. These phenomena manifest when certain factors alter the statistical properties of model inputs or outputs. The causes of concept drift are diverse and depend on the underlying context of the application or use case.

Data Drift

Data Drift Computer Vision Machine Learning Algorithm

The AI Feedback Loop: Maintaining Model Production Quality In The Age Of AI-Generated Content

Unite.AI

JULY 25, 2023

Production-deployed AI models need a robust and continuous performance evaluation mechanism. This is where an AI feedback loop can be applied to ensure consistent model performance. But, with the meteoric rise of Generative AI , AI model training has become anomalous and error-prone.

AI AI Data Drift AI Modeling

Artificial Intelligence Zone

Concept Drift vs Data Drift: How AI Can Beat the Change

The AI Feedback Loop: Maintaining Model Production Quality In The Age Of AI-Generated Content

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