R data analysis and visualization : a course in five modules

Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques w...

Descripción completa

Detalles Bibliográficos
Otros Autores: Fischetti, Tony, author (author), Lantz, Brett, author, Abedin, Jaynal, author, Mittal, Hrishi, author, Makhabel, Bater, author, Berlinger, Edina, author, Illés, Ferenc, author, Badics, Milán, author, Banai, Ádám, author, Daróczi, Gergely, author, Dömötör, Barbara, author, Gabler, Gergely, author, Havran, Dániel, author, Juhász, Péter, author, Margitai, István, author, Márkus, Balázs, author, Medvegyev, Péter, author, Molnár, Julia, author, Szucs, Balázs, author, Tuza, Ágnes, author, Vadász, Tamás, author, Váradi, Kata, author, Vidovics-Dancs, Ágnes, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham : Packt Publishing 2016.
Edición:1st edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629865606719
Descripción
Sumario:Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R p...
Notas:"Master the art of building analytical models using R with your course guide Edwin Moses."
"Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language."
Descripción Física:1 online resource (1,783 pages) : color illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9781786460486