This course introduces applications and techniques for assaying and modeling large data. The course also presents basic and advanced modeling strategies, such as group-by processing for linear models, random forests, generalized linear models, and mixture distribution models. Students perform hands-on exploration and analyses using tools such as SAS Enterprise Miner, SAS Visual Statistics, and SAS In-Memory Statistics.
Aprenda a
- Use applications designed for big data analyses.
- Explore data efficiently.
- Reduce data dimensionality.
- Build predictive models using decision trees, regressions, generalized linear models, random forests, and support vector machines.
- Build models that handle multiple targets.
- Assess models using validation and cross-validation techniques.
- Implement models and score new predictions.
A quién va dirigido
Business analysts, data analysts, marketing analysts, marketing managers, data scientists, data engineers, financial analysts, data miners, statisticians, and others who work in related fields
Formatos disponibles | Duración | | |
e-learning: |
17.5 horas/180 día licencia |
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Before attending this course, participants should have at least an introductory-level familiarity with basic statistics and linear models. Previous SAS software experience is helpful but not required.
Este curso utiliza SAS Enterprise Miner, SAS Visual Statistics, SAS In-Memory Statistics software.
