SAS Viya Supervised Machine Learning Pipelines
This SAS Viya Supervised Machine Learning Pipelines covers the theoretical foundation for different techniques associated with supervised machine learning models. In addition, the business case study is defined to convey the participants through steps of the analytical life cycle, from the issue understanding to model deployment, through information preparation, feature selection, model training and validation, and model assessment.
A series of demonstrations and exercises are used to reinforce the concepts and the analytical approach to solving business problems. This training course uses Model Studio, the pipeline flow interface in SAS Viya that empowers you to prepare, develop, compare, and deploy the advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data. The SAS apps used in this course make machine learning possible without coding.
Module 1: Data Sources (30%)
Module 2: Building Models (50%)
Module 3: Model Assessment and Deployment (20%)
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