docs.datarobot.com

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• content: Public documentation for DataRobot’s end-to-end AI platform. Access platform and API docs, tutorial content, and more from a single location. name: description
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• ¶
• Release notes for January are available
• DataRobot docs
• Feedback
• Get Started
• Generative AI
• Agentic AI
• NextGen UI
• Applications
• Developer docs
• Account management
• Releases
• Installation
• Reference
• For Self-Managed AI Platform users running v11.1, see the on-premise platform documentation
• Data
• Data connections
• Share secure configurations
• Data connections
• AI Catalog
• Load data
• Manage assets
• Work with assets
• Schedule snapshots
• Prepare data with Spark SQL
• Import data
• Import to DataRobot directly
• Large datasets
• Fast EDA for large datasets
• Transform data
• Interaction-based transformations
• Feature Discovery
• End-to-end Feature Discovery
• Set up Feature Discovery projects
• Snowflake integration
• Feature Discovery settings
• Time-aware feature engineering
• Derived features
• Predictions
• Manual transformations
• Analyze data
• Assess data quality with EDA
• Analyze features using histograms
• Analyze frequent values
• Feature details
• Exploratory Spatial Data Analysis (ESDA)
• Feature Associations
• Use data pipelines for ingest and transformation
• Data preview features
• Create feature lists in the Relationship Editor
• Data FAQ
• Modeling
• Build models
• Build models
• Basic model workflow
• Work with feature lists
• Unlock Holdout
• Comprehensive Autopilot
• Add/delete models
• Frozen runs
• Model Repository
• Advanced options
• Additional
• Bias and Fairness
• Clustering advanced options
• External Predictions
• Feature Constraints
• Image Augmentation
• Partitioning
• Smart Downsampling
• Time series
• GPUs for deep learning
• Model insights
• Evaluate
• Accuracy Over Space
• Accuracy Over Time
• Advanced Tuning
• Anomaly visualizations
• Confusion Matrix (for multiclass models)
• Forecasting Accuracy
• Forecast vs Actual
• Lift Chart
• Period Accuracy
• Residuals
• ROC Curve tools
• Use the ROC Curve tools
• Select data and display threshold
• Confusion matrix
• Prediction Distribution graph
• ROC curve
• Profit curve
• Cumulative Charts
• Custom charts
• Metrics
• Series Insights (clustering)
• Series Insights (multiseries)
• Stability
• Training Dashboard
• Understand
• Cluster Insights
• Feature Effects
• Feature Impact
• Prediction Explanations
• Prediction Explanations overview
• SHAP Prediction Explanations
• XEMP Prediction Explanations
• Text Prediction Explanations
• Prediction Explanations for clusters
• Prediction Explanations for time-aware projects
• Word Cloud
• Describe
• Blueprint
• Blueprint JSON
• Coefficients (preprocessing)
• Constraints (monotonic)
• Data Quality Handling Report
• Eureqa Models
• Log
• Model Info
• Rating Tables
• Predict
• Deploy
• Downloads
• Make Predictions
• Portable Predictions
• Compliance
• Model Compliance
• Template Builder for compliance reports
• Comments
• Bias and Fairness
• Cross-Class Accuracy
• Cross-Class Data Disparity
• Per-Class Bias
• Other
• Bias vs Accuracy
• Insights
• Learning Curves
• Model Comparison
• Speed vs Accuracy
• Specialized workflows
• Bias and Fairness resources
• Composable ML
• Composable ML overview
• Composable ML Quickstart
• Modify a blueprint
• Create custom tasks
• Custom environments
• DRUM CLI tool
• Enable network access for custom tasks
• Document AI
• Document AI overview
• Document ingest and modeling
• Document AI insights
• Predictions from documents
• Location AI
• Data ingest
• Exploratory Spatial Data Analysis (ESDA)
• Modeling
• Unsupervised learning
• Anomaly detection
• Clustering
• Visual AI
• Visual AI overview
• Build Visual AI models
• Train-time image augmentation
• About augmented models
• Transformations and lists
• Use case examples
• Model insights
• Tune models
• Visual AI predictions
• Multilabel modeling
• Out-of-time validation modeling
• Text AI resources
• Time-series modeling
• What is time-aware modeling?
• Time series modeling
• Time series insights
• Time series predictions
• Time series portable predictions with prediction intervals
• Multiseries modeling
• Clustering
• Segmented modeling
• Nowcasting
• External prediction comparison
• Batch predictions for TTS and LSTM models
• Time series advanced modeling
• Time series advanced options
• Clustering advanced options
• Date/time partitioning advanced options
• Customizing time series projects
• Time series modeling data
• Create the modeling dataset
• Data prep for time series
• Restore features removed by reduction
• AutoML preview features
• Quantile regression analysis
• Configure hyperparameters for custom tasks
• Modeling FAQ
• Value Tracker
• Project control center
• Predictions
• Real-time scoring methods
• Prediction API snippets
• Qlik predictions
• Batch prediction methods
• Batch prediction UI
• Make a one-time batch prediction
• Schedule recurring batch prediction jobs
• Manage prediction job definitions
• Snowflake prediction job examples
• Prediction monitoring jobs
• Create monitoring jobs
• Monitoring jobs API
• Manage monitoring job definitions
• Manage batch jobs
• Batch prediction scripts
• Portable prediction methods
• Scoring Code
• Download Scoring Code from the Leaderboard
• Download Scoring Code from a deployment
• Download Scoring Code from the Leaderboard (Legacy)
• Scoring Code for time series projects
• Scoring at the command line
• Scoring Code usage examples
• JAR structure
• Generate Java models in an existing project
• Backward-compatible Java API
• Scoring Code JAR integrations
• Android integration
• Portable Prediction Server
• Portable Prediction Server configuration
• Portable Prediction Server running modes
• Portable batch predictions
• Custom model Portable Prediction Server
• DataRobot Prime (deprecated)
• Predictions testing
• Predictions reference
• MLOps
• Deployment
• Deployment workflows
• DataRobot model in a DataRobot environment
• DataRobot model in a PPS
• Custom model in a DataRobot environment
• Custom model in a PPS
• Scoring Code in an external environment
• Monitor an external model with the monitoring agent
• Register models
• Model Registry
• Register DataRobot models
• Register custom models
• Register external models
• Deploy registered models
• View and manage registered models
• Generate model compliance documentation
• Extend compliance documentation with key values
• Custom jobs
• Import model packages into MLOps
• Model logs for model packages (legacy)
• Prepare custom models for deployment
• Custom Model Workshop
• Create custom inference models
• Manage custom model dependencies
• Manage custom model resources
• Add custom model versions
• Add training data to a custom model
• Add files from remote repos to custom models
• Test custom models
• Manage custom models
• Register custom models
• Create custom model proxies for external models
• GitHub Actions for custom models
• Custom model environments
• Drop-in environments
• Custom environments
• Prepare for external model deployment
• Add external prediction environments
• Manage prediction environments
• Register external models
• Manage prediction environments
• Add DataRobot Serverless prediction environments
• Add external prediction environments
• Manage prediction environments
• Deploy a model to a prediction environment
• Prediction environment integrations
• Automated deployment and replacement of Scoring Code in AzureML
• Automated deployment and replacement in Sagemaker
• Deploy models
• Deploy DataRobot models
• Deploy custom models
• Deploy external models
• Configure deployment settings
• Add prediction data post-deployment
• MLOps agents
• Monitoring agent
• Installation and configuration
• Examples directory
• Monitoring agent use cases
• Environment variables
• Library and agent spooler configuration
• Download Scoring Code
• Monitoring external multiclass deployments
• Management agent
• Installation and configuration
• Configure environment plugins
• Install the management agent for Kubernetes
• Management agent deployment status and events
• Relaunch deployments
• Force delete deployments
• Agent event log
• Deployment settings
• Set up service health monitoring
• Set up data drift monitoring
• Set up accuracy monitoring
• Set up fairness monitoring
• Set up humility rules
• Configure retraining
• Configure challengers
• Configure predictions settings
• Enable data exploration
• Set up custom metrics monitoring
• Set up timeliness tracking
• Lifecycle management
• Deployment inventory
• Manage deployments
• Replace deployed models
• Manage Automated Retraining policies
• Performance monitoring
• Overview tab
• Accuracy tab
• Data Drift tab
• Service Health tab
• Challengers tab
• Usage tab
• Data Exploration tab
• Custom Metrics tab
• Segmented analysis
• Batch monitoring
• Generative model monitoring
• Governance
• Model deployment approval workflow
• Governance lens
• Notifications tab
• Humility tab
• Fairness tab
• Deployment reports
• MLOps preview features
• Service Health and Accuracy history
• Automated deployment and replacement of Scoring Code in Snowflake
• Run the monitoring agent in DataRobot
• Feature cache for Feature Discovery deployments
• MLOps reporting for unstructured models
• MLOps FAQ
• Notebooks
• Manage notebooks
• Add notebooks
• Notebook settings
• Notebook versioning
• Notebook coding experience
• Environment management
• Create and execute cells
• Cell actions
• Code intelligence
• Notebook terminals
• Azure OpenAI Service integration
• Notebook FAQ
• Integrations
• AWS
• Import data from AWS S3
• Deploy models on AWS EKS
• Path-based routing to PPS
• Score Snowflake data on AWS EMR Spark
• Ingest data with AWS Athena
• AWS Lambda
• AWS Lambda reporting to MLOps
• Use DataRobot Prime models with AWS Lambda
• Use Scoring Code with AWS Lambda
• Amazon SageMaker
• Deploy models on SageMaker
• Use Scoring Code with AWS SageMaker
• Azure
• Run Batch Prediction jobs from Azure Blob Storage
• Deploy and monitor DataRobot models in Azure Kubernetes Service
• Deploy and monitor Spark models with DataRobot MLOps
• Deploy and monitor ML.NET models with DataRobot MLOps
• Use Scoring Code with Azure ML
• Google
• Deploy and monitor models on GCP
• Deploy the MLOps agent on GKE
• Snowflake
• Data ingest and project creation
• Real-time predictions
• Server-side model scoring
• Snowflake external functions and streams
• Generate Snowflake UDF Scoring Code
• ¶
• ¶
• ¶
• ¶
• ¶
• ¶
• ¶
• ¶
• ¶
• ¶
• Access documentation for the Classic DataRobot UI experience

• Start a free trial
• DataRobot YouTube
• DataRobot.com
• Legal
• Privacy
• Trust
• Status

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