IBM Cloud Pak for Watson Machine Learning
GPTKB entity
Statements (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Cloud_Computing_Service
|
| gptkbp:developedBy |
gptkb:IBM
|
| gptkbp:enables |
data governance
data integration real-time predictions collaborative data analysis |
| gptkbp:facilitates |
model monitoring
|
| https://www.w3.org/2000/01/rdf-schema#label |
IBM Cloud Pak for Watson Machine Learning
|
| gptkbp:includes |
data preparation tools
|
| gptkbp:integratesWith |
gptkb:IBM_Watson
|
| gptkbp:isAvailableIn |
gptkb:IBM_Cloud
multi-cloud deployment on-premises deployment hybrid cloud deployment |
| gptkbp:isCompatibleWith |
Docker
Kubernetes |
| gptkbp:isDesignedFor |
enterprise applications
|
| gptkbp:isIntegratedWith |
gptkb:IBM_Watson_Knowledge_Catalog
gptkb:IBM_Cloud_Object_Storage gptkb:IBM_Db2 |
| gptkbp:isOptimizedFor |
large datasets
|
| gptkbp:isPartOf |
gptkb:IBM_AI_portfolio
gptkb:IBM_Cloud_Pak AI lifecycle management |
| gptkbp:isUsedBy |
business analysts
data scientists |
| gptkbp:isUsedIn |
healthcare
telecommunications finance manufacturing retail |
| gptkbp:offers |
customizable solutions
scalability user-friendly interface automated model deployment |
| gptkbp:offersPrograms |
gptkb:Apache_Spark
|
| gptkbp:provides |
data lineage tracking
data visualization tools performance monitoring security features machine learning capabilities model evaluation tools model training API_access |
| gptkbp:providesAccessTo |
gptkb:IBM_Watson_Studio
|
| gptkbp:providesSupportFor |
Python
R |
| gptkbp:supports |
data enrichment
data science data privacy compliance collaborative workflows automated machine learning multiple cloud environments model retraining model explainability |
| gptkbp:utilizes |
AI algorithms
|