Oracle Data Science Platform
GPTKB entity
Statements (73)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Company
|
| gptkbp:developedBy |
gptkb:Oracle_Corporation
|
| gptkbp:enables |
data preparation
data sharing predictive analytics AI model training data exploration data science education experiment tracking model monitoring business analytics |
| gptkbp:facilitates |
team collaboration
model deployment |
| gptkbp:features |
data lineage tracking
data visualization tools user-friendly interface version control interactive dashboards automated data preparation data science frameworks data storytelling tools |
| https://www.w3.org/2000/01/rdf-schema#label |
Oracle Data Science Platform
|
| gptkbp:includes |
notebooks
pre-built algorithms |
| gptkbp:integratesWith |
gptkb:Oracle_Cloud_Infrastructure
gptkb:Oracle_Exadata gptkb:Oracle_Analytics_Cloud gptkb:Oracle_Cloud_Applications gptkb:Oracle_Data_Cloud gptkb:Oracle_Machine_Learning gptkb:Oracle_Data_Science_Cloud third-party tools |
| gptkbp:offers |
community support
customizable workflows training resources cloud-based solutions cloud-native architecture data governance tools automated machine learning enterprise-grade security data science certifications API_access |
| gptkbp:provides |
data insights
real-time data processing scalability model evaluation tools collaboration features data analytics solutions data quality tools data integration capabilities data access capabilities business intelligence capabilities collaborative data science tools |
| gptkbp:supports |
Python
R machine learning Jupyter notebooks data security data-driven decision making multi-cloud environments real-time analytics collaborative projects big data analytics data lakes data modeling open-source tools data wrangling data science research data science teams data science lifecycle data-driven innovation data science best practices |
| gptkbp:utilizes |
gptkb:Oracle_Autonomous_Database
|