Metaflow Flows

GPTKB entity

Statements (74)
Predicate Object
gptkbp:instance_of gptkb:website
gptkbp:allows data versioning
local execution
gptkbp:constructed_in data-driven applications
Python libraries
gptkbp:developed_by gptkb:streaming_service
gptkb:Library
data engineers
gptkbp:enables gptkb:collaboration
scalability
model deployment
reproducibility
gptkbp:facilitates data exploration
experiment tracking
gptkbp:features data artifacts
https://www.w3.org/2000/01/rdf-schema#label Metaflow Flows
gptkbp:includes step decorators
gptkbp:integrates_with gptkb:AWS
gptkbp:is_available_on gptkb:archive
gptkbp:is_compatible_with gptkb:lake
gptkb:fortification
gptkb:Cloud_Computing_Service
data lakes
data warehouses
gptkbp:is_designed_for iterative development
complex workflows
end-to-end workflows
gptkbp:is_designed_to enhance productivity
simplify workflows
gptkbp:is_documented_in official documentation
gptkbp:is_integrated_with data analytics tools
data storage solutions
data processing frameworks
ML frameworks
gptkbp:is_known_for flexibility
scalability
robustness
ease of use
gptkbp:is_optimized_for large datasets
gptkbp:is_part_of data engineering
AI development
data science ecosystem
machine learning lifecycle
data science toolkit
data science frameworks
gptkbp:is_supported_by gptkb:Community_Center
gptkbp:is_used_by data scientists
gptkbp:is_used_for data modeling
model training
data science workflows
gptkbp:is_used_in gptkb:academic_research
production environments
gptkbp:is_utilized_in gptkb:software
business analysts
data analysis
research teams
gptkbp:offers cloud integration
data management tools
data pipeline management
gptkbp:provides data visualization tools
user-friendly interface
versioning
automatic scaling
logging capabilities
easy deployment
gptkbp:supports gptkb:Library
gptkb:Jupyter_notebooks
team collaboration
data transformation
hyperparameter tuning
real-time analytics
batch processing
gptkbp:bfsParent gptkb:DGX_A100
gptkbp:bfsLayer 5