- Overview
- Introduction to Platform
- A customer experience powered by Experience Platform
- Behind the scenes: A customer experience powered by Experience Platform
- Experience Platform overview
- Key capabilities
- Application and Intelligent Services
- Integrations with Experience Cloud applications
- Key use cases
- Basic architecture
- Using the Platform user interface
- Roles and project phases
- Authenticate to Experience Platform APIs
- Getting started: Data Architects and Data Engineers
- Import sample data to Experience Platform
- Data Governance
- Data Ingestion
- Overview
- Batch ingestion overview
- Create and populate a dataset
- Map a CSV file to XDM
- Streaming ingestion overview
- Create an authenticated streaming connection
- Create a streaming connection (UI)
- Create a streaming connection (API)
- Streaming record data
- Streaming time series data
- Streaming multiple messages
- Dataflow monitoring
- Monitoring dashboard
- Web SDK tutorials
- Mobile SDK tutorials
- Debugger tutorials
- Data Science Workspace
- Overview
- Architecture
- Load data in JupyterLab notebooks
- Train, score and productize models with the recipe builder template
- Create and publish a machine learning model
- Create the Retail Sales schema and dataset
- Preview schemas and datasets
- Package source files into a recipe
- Import a packaged recipe (UI)
- Import a packaged recipe (API)
- Optimize a model
- Enrich Real-time Customer Profile with machine learning insights
- Publish a model as a service (UI)
- Publish a model as a service (API)
- Schedule automated training and scoring on a service
- Destinations
- Identities
- Profiles
- Queries
- Sandboxes
- Schemas
- Segments
- Sources
- Application Services
- Intelligent Services
- Experience Cloud Integrations
Data Science Workspace architecture overview
This video walks through an overview diagram and explains the primary components of Experience Platform as it relates to Data Science Workspace.
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