II.
LibraryProcess overview
Reference · livelib-process:data-science-ml--automl-pipeline
specializations/data-science-ml/automl-pipeline overview
AutoML Pipeline Orchestration - Automated machine learning workflows with algorithm selection, hyperparameter optimization, ensemble creation, and model selection with human-in-the-loop validation gates.
Attributes
displayName
specializations/data-science-ml/automl-pipeline
description
AutoML Pipeline Orchestration - Automated machine learning workflows with algorithm selection,
hyperparameter optimization, ensemble creation, and model selection with human-in-the-loop validation gates.
libraryPath
library/specializations/data-science-ml/automl-pipeline.js
specialization
data-science-ml
references
- - Auto-sklearn: https://automl.github.io/auto-sklearn/
- - H2O AutoML: https://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html
- - MLflow Experiment Tracking: https://mlflow.org/
- - Google AutoML: https://cloud.google.com/automl
example
const result = await orchestrate('specializations/data-science-ml/automl-pipeline', {
dataPath: 'data/training.csv',
targetColumn: 'churn',
problemType: 'binary-classification',
timeLimit: 3600,
targetMetric: 'auc'
});
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_workflow2
- workflow:release-management·WorkflowRelease Management Workflow
- workflow:data-pipeline-deployment·WorkflowData Pipeline Deployment
Incoming edges
None.