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Data science, analytics and 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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: F�avero, Luiz Paulo (Autor), Belfiore, Patr�icia Prado (Autor), De Freitas Souza, Rafael (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, [2023]
Edición:Fisrt edition.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a F�avero, Luiz Paulo,  |e author. 
245 1 0 |a Data science, analytics and machine learning with R /  |c Luiz Paulo F�avero, Patr�icia Belfiore, Rafael de Freitas Souza. 
250 |a Fisrt edition. 
264 1 |a London :  |b Academic Press,  |c [2023] 
264 4 |c �2023 
300 |a 1 online resource (558 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
588 |a Description based on online resource; title from digital title page (viewed on March 22, 2023). 
520 |a 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. 
520 |a Key Features- Presents a comprehensive and practical overview of machine learning, data mining and AI techniques for a broad multidisciplinary audience- Serves readers who are interested in statistics, analytics and modeling, and those who wish to deepen their knowledge in programming through the use of R- Teaches readers how to apply machine learning techniques to a wide range of data and subject areas- Presents data in a graphically appealing way, promoting greater information transparency and interactive learning. 
650 0 |a Business  |x Data processing. 
650 0 |a Machine learning. 
650 0 |a R (Computer program language) 
650 6 |a Gestion  |x Informatique.  |0 (CaQQLa)201-0033709 
650 6 |a Apprentissage automatique.  |0 (CaQQLa)201-0131435 
650 6 |a R (Langage de programmation)  |0 (CaQQLa)201-0368319 
650 7 |a Business  |x Data processing  |2 fast  |0 (OCoLC)fst00842293 
650 7 |a Machine learning  |2 fast  |0 (OCoLC)fst01004795 
650 7 |a R (Computer program language)  |2 fast  |0 (OCoLC)fst01086207 
700 1 |a Belfiore, Patr�icia Prado,  |e author. 
700 1 |a De Freitas Souza, Rafael,  |e author 
776 0 8 |a FAVERO, LUIZ PAULO. BELFIORE, PATRICIA. DE FREITAS SOUZA, RAFAEL.  |t DATA SCIENCE, ANALYTICS AND MACHINE LEARNING WITH R.  |d [S.l.] : ELSEVIER ACADEMIC PRESS, 2022  |z 012824271X  |w (OCoLC)1286790517 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128242711  |z Texto completo