II.
LibraryProcess overview
Reference · livelib-process:data-science-ml--ml-project-scoping
ml-project-scoping overview
ML Project Scoping and Requirements Analysis - Define business objectives, success metrics, constraints, and technical requirements for ML projects with feasibility assessment and stakeholder alignment.
Attributes
displayName
ml-project-scoping
description
ML Project Scoping and Requirements Analysis - Define business objectives, success metrics,
constraints, and technical requirements for ML projects with feasibility assessment and stakeholder alignment.
libraryPath
library/specializations/data-science-ml/ml-project-scoping.js
specialization
data-science-ml
references
- - CRISP-DM Methodology: https://www.datascience-pm.com/crisp-dm-2/ - Team Data Science Process (TDSP): https://learn.microsoft.com/en-us/azure/architecture/data-science-process/overview - MLOps Principles: https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning - Rules of Machine Learning - Google: https://developers.google.com/machine-learning/guides/rules-of-ml
example
const result = await orchestrate('specializations/data-science-ml/ml-project-scoping', {
projectName: 'Customer Churn Prediction',
businessDomain: 'E-commerce',
stakeholders: ['Product Manager', 'Data Science Lead', 'Engineering Lead'],
initialRequirements: 'Predict customer churn to enable proactive retention campaigns'
});
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.