https://devlaravel.imosver.com/en/libros/data-scienceanalytics-machine-learning-with-r-00103546210010354621DATA SCIENCE,ANALYTICS MACHINE LEARNING WITH R129.43Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The bookhttps://static.arnoia.com/imagenes_small/9780128/978012824271.jpgLibrosLibros/TECNOLOGIAEn stockACADEMIC PRESS000https://static.arnoia.com/imagenes_small/9780128/978012824271.jpg001030662100102617690010246626136.2456.812022/11/019780128242711FAVEROLibrosaño_2022idioma_EnglishIautor_FAVEROsaga_SIN COLECCION
Artículo
DATA SCIENCE,ANALYTICS MA
FAVERO
ACADEMIC PRESS
TECNOLOGIA
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Synopsis DATA SCIENCE,ANALYTICS MACHINE LEARNING WITH R
Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. ear.