Supervised Machine Learning Using SAS Viya in SAS Studio
8.30am to 5.30pm
S$2,800 (excl of G.S.T)
|2020 Course Dates
15 – 16 Oct 2020
|None of the published dates will work for you? Speak to our training consultants for a private tuition arrangement or a closed door training.|
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.
• 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.
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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