This course combines theory and practice to immerse you in the core concepts of neural network models and the essential practices of real-world application. During the course, you programmatically build a neural network and discover how to adjust the model’s essential parameters to solve different types of business challenges. You implement early stopping, build autoencoders for a predictive model, and perform an intelligent automatic search of the model hyperparameter values. The last lesson introduces deep learning. You gain hands-on practice building neural networks in SAS 9.4 and the cutting-edge cloud computing platform for big data analytics, SAS Viya.
Learn how to
- Programmatically build neural networks in SAS 9.4 and SAS Viya.
- Modify neural networks' parameters for better performance.
- Conduct automatic search for neural networks' hyperparameters through genetic algorithm.
- Enhance data with autoencoders and synthetic observations.
Who should attend
Those interested in learning about neural networks, general machine learning and data science techniques, and SAS software
Formats available | Standard Duration (duration can vary, see event schedule for details) | | |
Classroom: |
2.0 days | | |
e-Learning: |
10.5 hours/180 day license |
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Before taking this course, you should have the following:
- Some familiarity with programming in SAS or SQL (or both).
- An understanding of predictive modeling.
- A basic understanding of calculus.
This course addresses SAS Viya software.
