II.
SkillArea overview
Reference · liveskill-area:feature-engineering-pipelines
Data and Feature Engineering Pipelines overview
Building pipelines that derive training and serving features - feature extraction, transformation reuse, consistency, and lifecycle management.
Attributes
displayName
Data and Feature Engineering Pipelines
description
Building pipelines that derive training and serving features - feature
extraction, transformation reuse, consistency, and lifecycle management.
domains
expertiseLevels
- intermediate
- expert
Outgoing edges
applies_to2
- domain:ml-ops·DomainMLOps
- specialization:data-engineering-analytics·Specialization
requires_skill_area1
- skill-area:data-preprocessing·SkillAreaData Preprocessing
uses_stack_part1
- stack-part:feature-store·StackPartFeature Store
Incoming edges
lib_requires_skill_area6
- lib-agent:data-engineering-analytics--ml-feature-engineer·LibraryAgentML Feature Engineer Agent
- lib-agent:data-science-ml--feature-engineer·LibraryAgentfeature-engineer
- lib-agent:data-science-ml--feature-store-engineer·LibraryAgentfeature-store-engineer
- lib-agent:data-science-ml--model-trainer·LibraryAgentmodel-trainer
- lib-skill:data-engineering-analytics--feature-engineering-optimizer·LibrarySkillFeature Engineering Optimizer
- lib-skill:data-science-ml--feast-feature-store·LibrarySkillfeast-feature-store
prerequisite_for_learning2
- skill-area:machine-learning·SkillAreaMachine Learning
- skill-area:feature-engineering-production·SkillAreaProduction Feature Engineering
requires_skill_area2
- stack-profile:feature-store-mlops·StackProfileFeature Store & MLOps Stack (Feast, MLflow, BentoML, K8s, Prometheus)
- workflow:model-training-pipeline·WorkflowModel Training Pipeline