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| Section | Objectives |
|---|---|
| Process Big Data | - Process data with rxDataStep - Perform complex transforms using transform functions - Process text using MicrosoftML packages - Manage data sets |
| Use R Server in Different Environments | - Perform in-database analytics using SQL Server - Use different compute contexts to run R Server effectively - Optimize tasks using local compute contexts - Deploy predictive models to SQL Server and Azure Machine Learning - Implement analysis workflows in Hadoop and Spark |
| Read and Explore Big Data | - Read data with R Server - Visualize data - Summarize data |
| Build Predictive Models with ScaleR | - Build and use partitioning models - Generate predictions and residuals - Evaluate models and tuning parameters - Estimate linear models - Create additional models using MicrosoftML packages |
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