This course covers the theoretical foundation for different techniques associated with supervised machine learning models. In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment. A series of demonstrations and exercises is used to reinforce the concepts and the analytical approach to solving business problems.
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There are 9 modules in this course
In this module, you meet the instructor and learn about course logistics, such as how to access the software for this course.
What's included
1 video3 readings1 app item
In this module, you learn how you can meet today's business challenges with machine learning using SAS® Viya®. You start working on the project that runs throughout the course.
What's included
13 videos17 readings6 assignments3 app items
In this module, you learn to explore the data and finish preparing the data for analysis. You also learn some general considerations for selecting an algorithm.
What's included
14 videos12 readings8 assignments6 app items
In this module, you learn to build decision tree models as well as models based on ensembles, or combinations, of decision trees.
What's included
23 videos17 readings11 assignments6 app items
In this module, you learn to build neural network models.
What's included
19 videos11 readings6 assignments3 app items
In this module, you learn to build support vector machine models.
What's included
17 videos7 readings5 assignments4 app items
In this module, you learn how to select the model that best meets the requirements of your business challenge and put the model into production. You also learn about managing the model over time.
What's included
17 videos8 readings6 assignments6 app items
What's included
2 videos4 readings1 app item
What's included
1 app item
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Recommended if you're interested in Machine Learning
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