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| Section | Objectives |
|---|---|
| Topic 1: Build Predictive Models with ScaleR | - Estimate linear models - Generate predictions and residuals - Build and use partitioning models - Create additional models using MicrosoftML packages - Evaluate models and tuning parameters |
| Topic 2: Read and Explore Big Data | - Read data with R Server - Summarize data - Visualize data |
| Topic 3: Use R Server in Different Environments | - Use different compute contexts to run R Server effectively - Perform in-database analytics using SQL Server - Deploy predictive models to SQL Server and Azure Machine Learning - Optimize tasks using local compute contexts - Implement analysis workflows in Hadoop and Spark |
| Topic 4: Process Big Data | - Perform complex transforms using transform functions - Process text using MicrosoftML packages - Manage data sets - Process data with rxDataStep |
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