- Overview
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- Data Science Workspace
- Overview
- Architecture
- Load data in JupyterLab notebooks
- Query and discover data in JupyterLab notebooks
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- Recipes, models, and services overview
- Build a model using the recipe builder template
- Analyze model performance
- Create and publish a trained model (UI)
- Schedule automated training and scoring for a service
- Enrich Real-time Customer Profiles with machine learning insights
- Package source files into a recipe
- Import a packaged recipe (UI)
- Import a packaged recipe (API)
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- Integrate with Google Customer Match
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- Activate data to non-Adobe applications webinar
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- Industry Trends
Query and discover data in Data Science Workspace
Adobe Experience Platform allows you to use Structured Query Language (SQL) in Data Science Workspace by integrating Query Service into JupyterLab as a standard feature. This tutorial demonstrates some common use cases to explore, transform, and analyze data.
INFO
This video is part of a course, Getting Started with Data Science Workspace for Data Scientists, available for free on Experience League!
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