SOWA OPAC : Biblioteka Publiczna Miasta i Gminy Wolsztyn im. Stanisława Platera

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R: Data Analysis and Visualization. Click here to enter text / Tony Fischetti, Brett Lantz, Jaynal Abedin, Hrishi V. Mittal, Bater Makhabel, Edina Berlinger (EURO), Ferenc Illés, Ádám Banai, Gergely Daróczi, Barbara Dömötör, Gergely Gabler, Dániel Havran, Péter Juhász, Margitai István, Ágnes Tuza, Milán Badics, Kata Váradi, István Margitai, Péter Medvegyev, Agnes Vidovics-Dancs, Julia Molnár, Balázs Árpád Sz?+-cs, Balázs Márkus, Tamás Vadász. - [miejsce nieznane] : Packt Publishing : ebookpoint BIBLIO, 2016.

Autor

Fischetti Tony. Lantz Brett. Abedin Jaynal. Mittal Hrishi V. Makhabel Bater. Berlinger Edina. Illés Ferenc. Banai Ádám. Daróczi Gergely. Dömötör Barbara. Gabler Gergely. Havran Dániel. Juhász Péter. István Margitai. Tuza Ágnes. Badics Milán. Váradi Kata. Margitai István. Medvegyev Péter. Vidovics-Dancs Agnes. Molnár Julia. Sz?+-cs Balázs Árpád. Márkus Balázs. Vadász Tamás.

Forma i typ

E-booki

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 programs.The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions.Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on.

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