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|a 1158228564
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|a Machine learning with SAS Viya /
|c SAS Institute.
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|a Cary, North Carolina :
|b SAS Institute Inc.,
|c 2020.
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|a 1 online resource :
|b color illustrations
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|a Based on the SAS training course Machine Learning Using SAS Viya, developed by Carlos Pinheiro, Andy Ravenna, Sharad Saxena, Jeff Thompson, Marya Ilgen-Lieth, and Cat Truxillo.
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|a Introduction to machine learning -- Preparing your data: introduction -- Preparing your data: missing and unstructured data -- Preparing your data: extract features -- Discovery: selecting an algorithm -- Decision trees: introduction -- Decision trees: improving the model -- Decision trees: ensemble and forests -- Neural networks: introduction and model architecture -- Neural networks: optimizing the model and learning -- Support vector machines -- Model assessments and deployment -- Additional model manager tools and open-source code.
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|a Master machine learning with SAS Viya! Machine learning can feel intimidating for new practitioners. Machine Learning with SAS Viya provides everything you need to know to get started with machine learning in SAS Viya, including decision trees, neural networks, and support vector machines. The analytics life cycle is covered from data preparation and discovery to deployment. Working with open-source code? Machine Learning with SAS Viya has you covered - step-by-step instructions are given on how to use SAS Model Manager tools with open source. SAS Model Studio features are highlighted to show.
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|a Includes bibliographical references.
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|f Copyright #169: SAS Institute
|g 2020
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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|a SAS (Computer file)
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|a Machine learning.
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|a Computer algorithms.
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|a Algorithms
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|a Machine Learning
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|a Apprentissage automatique.
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|a Algorithmes.
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|a algorithms.
|2 aat
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|a Computer algorithms
|2 fast
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|a Machine learning
|2 fast
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710 |
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|a SAS Institute.
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|i Print version:
|a Machine Learning with SAS Viya
|d Cary, NC : SAS Institute, ©2020
|z 9781951685300
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|u https://learning.oreilly.com/library/view/~/9781951685379/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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