SAS Model Manager
| Título | Nível | Formatos de Treinamento |
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Managing Models in SAS® Viya®
This applied, hands-on course teaches you how to manage models through their useful life cycle. You start by creating a modeling project, and then you add and compare models to it so that you can identify a champion model. The course uses models that are created using SAS Advanced Analytics capabilities and Python and R languages. The course also shows how to implement procedures that ensure that model governance and oversight approval is being followed by implementing workflow. You learn how to test a model in the production environment to which it will be deployed. After the model test runs successfully, you learn how to schedule the model to run automatically. Further, the course shows how to measure and monitor the ongoing performance of model accuracy over time. The performance monitoring process will also be scheduled to run automatically in class. An optional lesson shows how to register and score four types of SAS Visual Text Analytics models. |
3 Intermediário |   |
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Managing SAS® Analytical Models Using SAS® Model Manager Version 14.2
Este curso se concentra nas seguintes áreas: gestão de fontes de dados do Model Manager, criar um projeto no Model Manager, importar modelos para o Model Manager, usar o Model Manager Query Utility, criação de tarefas de pontuação, exportar modelos e projetos para o repositório SAS e criar e configurar versão de ciclos de vida. Este curso também ensina como criar e gerar relatórios de modelos de comparação, publicar e implantar modelos do Model Manager, criar modelos de acompanhamento de relatórios no Model Manager e criar relatórios definidos pelo usuário. |
3 Intermediário |  |
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Strategies and Concepts for Data Scientists and Business Analysts
To be effective in a competitive business environment, analytics professionals need to use descriptive, predictive, and prescriptive analytics to translate information into decisions. An effective analyst also should be able to identify the analytical tools and data structures to anticipate market trends. In this course, you gain the skills that data scientists and statistical business analysts must have to succeed in today's data-driven economy. Learn about visualizing big data, how predictive modeling can help you find hidden nuggets, the importance of experiments in business, and the kind of value you can gain from unstructured data. This course combines scheduled, instructor-led classroom or Live Web sessions with small-group discussion, readings, and hands-on software demonstrations, for a highly engaging learning experience. The self-study e-learning includes:
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3 Intermediário | |