Detail kurzu

Supervised Machine Learning Procedures Using SAS(R) Viya(R) in SAS(R) Studio

EDU Trainings s.r.o.

Popis kurzu

This course covers a variety of machine learning techniques that are performed in a scalable and in-memory execution environment. The course provides hands-on experience with SAS Visual Data Mining and Machine Learning through SAS Studio, a user interface for SAS programming. The machine learning techniques include logistic regression, decision tree and ensemble of trees (forest and gradient boosting), neural networks, support vector machine, factorization machine, and Bayesian networks. The self-study e-learning includes:Annotatable course notes in PDF format. Virtual lab time to practice.

Obsah kurzu

Introduction to SAS Viya, Data Preparation, and ExplorationIntroduction to machine learning and SAS Viya.Supervised machine learning concepts.RegressionIntroduction to regression.Categorical inputs.Interactions and polynomials.Selecting regression effects.Optimizing regression complexity.Interpreting regression models.Adjustments for oversampling.Decision TreeTree-structure models.Decision tree model essentials.Ensemble of trees.Neural NetworkIntroduction to neural networks.Neural network modeling essentials.Network architecture.Network learning.Model AssessmentModel assessment and comparison.Support Vector MachineIntroduction to support vector machines.Methods of solution.Bayesian NetworksIntroduction.Network structures.Factorization MachinesIntroduction to factorization machines.Selected Topics

Cílová skupina

Data analysts, data miners, mathematicians, statisticians, data scientists, citizen data scientists, qualitative experts, and others who want an introduction to supervised machine learning for predictive modeling
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