Data

Data integrity and quality are cornerstones for creating highly accurate predictive models. These sections describe the tools and visualizations DataRobot provides to ensure that your project doesn’t suffer the “garbage in, garbage out” outcome.

• Datasets
  • Create a dataset
  • Get information from a dataset
  • Retrieve datasets
  • Manage datasets
  • Manage dataset feature lists
• Database Connectivity
  • Creating Drivers
  • Creating DataStores
  • Creating DataSources
  • Creating Projects
  • Creating Predictions
• Feature Discovery
  • Register a primary dataset to start a project
  • Register secondary datasets in the AI Catalog
  • Create dataset definitions and relationships using helper functions
  • Create a relationship configuration
  • Create a Feature Discovery project
  • Create secondary dataset configuration for predictions
  • Make predictions with a trained model
  • Configure relationships
  • Dataset definitions and relationships using helper functions
  • Dataset definition and relationship using a dictionary
  • Retrieving relationship configuration
  • Update details of a relationship configuration
  • Delete relationships configuration
  • Secondary dataset configuration
  • Secondary datasets using helper functions
  • Create secondary datasets with dict
  • Create a secondary dataset configuration
  • Retrieve a secondary dataset configuration
  • List all secondary dataset configurations