Human In The Loop
Human-in-the-loop (HITL) is a machine learning design pattern in which human judgment is deliberately incorporated into a model's training, evaluation, or inference pipeline, rather than relying entirely on automation.
6 resources across 2 libraries
Glossary Terms(5)
Data Labeling
Data labeling is the process of assigning informative tags, categories, or ground-truth values to raw data so it can be used to train supervised machine learni…
Data Annotation
Data annotation is the process of enriching raw data with structured metadata — labels, tags, transcriptions, relationships, or attributes — so it can be used…
Human-in-the-Loop
Human-in-the-loop (HITL) is a machine learning design pattern in which human judgment is deliberately incorporated into a model's training, evaluation, or infe…
Model Monitoring
Model monitoring is the ongoing practice of tracking a deployed machine learning model's performance, input data characteristics, and predictions in production…
Concept Drift
Concept drift is the phenomenon where the statistical relationship between a model's input features and its target output changes over time, causing a previous…