There is a new version of this course. Please see Neural Networks: Essentials.
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.
Lernen Sie, wie Sie / 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.
Zielgruppe / Who should attend
Those interested in learning about neural networks, general machine learning and data science techniques, and SAS software
Verfügbare Schulungsformen / Formats available | Dauer | | |
Präsenzkurs: |
2.0 Tage | | |
|
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.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet: SAS Viya Software