Supervised Machine Learning Using SAS Viya in SAS Studio

Course Code:
SAS-DMML34

Duration:
2 days
8.30am to 5.30pm  
Course Fees:
S$2,800 (excl of G.S.T)
2020 Course Dates
15 – 16 Oct 2020
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Course Overview

This course combines data exploration, visualization, data preparation, feature engineering, sampling and partitioning, model training, scoring, and assessment. It covers a variety of statistical, data mining, and machine learning techniques performed in a scalable and in-memory execution environment. The course provides theoretical foundation and hands-on experience with SAS Visual Data Mining and Machine Learning through SAS Studio, a user interface for SAS programming. The course includes predictive modeling techniques such as linear and logistic regression, decision tree and ensemble of trees (forest and gradient boosting), neural networks, support vector machine, and factorization machine.

Program Objectives

• Create a SAS Cloud Analytic Services (CAS) session, and prepare and explore data for machine learning.

• Build linear and logistic regression models.

• Build decision tree, forest, and gradient boosting models.

• Build neural network models.

• Build support vector machine models.

• Build factorization machine models.

• Evaluate and compare model results.

• Score selected models.

Course Outline

Module 1: Introduction to SAS Viya, Data Preparation, and Exploration

Module 2: Regression

Module 3: Decision Tree

Module 4: Neural Network

Module 5: Support Vector Machine

Module 6: Model Assessment and Scoring

Module 7: Factorization Machines (Self-Study)

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