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[null,"1.","Record Nr.",null,"UNINA9910830474803321"]
[null,null,"Autore",null,"De Brouwer Philippe J. S."]
[null,null,"Titolo",null,"The big R-book : from data science to learning machines and big data / / Philippe J. S. De Brouwer"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, New Jersey : , : John Wiley & Sons, Inc., , 2021"]
[null,null,"ISBN",null,"1-119-63277-3"]
[{"$nulls":4},"1-119-63276-5"]
[{"$nulls":4},"1-119-63275-7"]
[null,null,"Descrizione fisica",null,"1 online resource (931 pages)"]
[null,null,"Disciplina",null,"519.502855133"]
[null,null,"Soggetti",null,"R (Computer program language)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","\"This book provides an overall introduction to R with a focus on tools and methods commonly used in Data Science, with an emphasis on practice and business use.The intention is to provide a practical guide for non-experts with a focus on business users. The author covers a wide range of topics in a single book: databases, statistical machine learning, data wrangling, data visualization, and reporting such results. The book includes seven parts. Part 1 is an Introduction, Part 2 provides an overview of R and elements of statistics. Part 3 revolves around data, while Part 4 focuses on data wrangling. Next, Part 5 focuses on exploring data. Modelling is covered in Part 6, while Part 7 covers reports. Finally, Part 7 contains appendices. The topics covered are all important for someone with a science/math background that is looking to quickly learn several practical technologies to enter or transition to the growing field of data science\"--"]