II.
LibraryProcess overview
Reference · livelib-process:data-science-ml--model-retraining
model-retraining overview
ML Model Retraining Pipeline - Detect model staleness, automatically retrain on updated data, validate performance improvements, deploy updated models, and maintain version lineage with quality gates
Attributes
displayName
model-retraining
description
ML Model Retraining Pipeline - Detect model staleness, automatically retrain on updated data,
validate performance improvements, deploy updated models, and maintain version lineage with quality gates
libraryPath
library/specializations/data-science-ml/model-retraining.js
specialization
data-science-ml
references
- - MLOps Continuous Training: https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning - Apache Airflow: https://airflow.apache.org/ - Prefect Modern Workflow: https://www.prefect.io/ - ML Test Score: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/aad9f93b86b7addfea4c419b9100c6cdd26cacea.pdf
example
const result = await orchestrate('data-science-ml/model-retraining', {
modelId: 'recommendation-model-v2',
retrainingTrigger: 'scheduled', // or 'drift-detected', 'performance-degradation'
dataSource: 's3://ml-data/training-data/2024-01-latest/',
performanceThreshold: 0.85,
autoDeployEnabled: false
});
usesAgents
- general-purpose
Outgoing edges
lib_applies_to_domain1
- domain:data-science·DomainData Science
lib_belongs_to_specialization1
- specialization:data-science-ml·Specialization
lib_implements_workflow1
- workflow:data-pipeline-deployment·WorkflowData Pipeline Deployment
lib_involves_role1
- role:data-scientist·RoleData Scientist
Incoming edges
None.