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Machine learning in R : automated algorithms for business analysis : applying K-Means clustering, decision trees, random forests, and neural networks /
"In the world of big data, analysis by traditional statistical methods is no longer sufficient. The amount of data and the number of potential relationships that could be analyzed is simply too complex to conduct manually. In this video, you'll learn a better way: how to automate the analy...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly,
[2018]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | "In the world of big data, analysis by traditional statistical methods is no longer sufficient. The amount of data and the number of potential relationships that could be analyzed is simply too complex to conduct manually. In this video, you'll learn a better way: how to automate the analysis of big data by using machine learning techniques in R. You'll explore the cornerstone methods of machine learning (i.e., k-means clustering, decision trees, random forests, and neural networks); you'll incorporate these methods inside R to construct a set of machine learning algorithms; and then you'll deploy these algorithms against a real-world dataset to perform a high-value business analysis of the data. Course prerequisites include basic knowledge of linear algebra, probability, statistics, and familiarity with R."--Resource description page |
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| Notas: | Title from title screen (viewed February 13, 2018). Date of publication from resource description page. |
| Descripción Física: | 1 online resource (1 streaming video file (38 min., 44 sec.)) |