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9por Peričić, Helena, 1961-
Publicado 2010Universidad Loyola - Universidad Loyola Granada (Otras Fuentes: Biblioteca de la Universidad Pontificia de Salamanca)Enlace del recurso
Libro electrónico -
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11Publicado 2019Libro electrónico
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12por Godin, Seth“…Most organizations are stuck in a rut. On one hand, they understand all the good things that will come with growth. …”
Publicado 2005
Grabación no musical -
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15Publicado 2017Libro electrónico
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16por Harris, EmmylouTabla de Contenidos: “…The pearl Michelangelo I don't wanna talk about it now Tragedy Red dirt girl My baby needs a shepherd Bang the drum slowly J'ai fait tout One big love Hour of gold My Antonia Boy from Tupelo…”
Publicado 2000
CDROM -
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19Publicado 2015Tabla de Contenidos: “…chapter 1. Little big data : mastering existing information as a foundation for big data / Donald A. …”
Libro electrónico -
20Publicado 2016Tabla de Contenidos: “…Cover -- Copyright -- Credits -- About the Author -- Acknowledgement -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: The Era of Big Data -- Big Data - The monster re-defined -- Big Data toolbox - dealing with the giant -- Hadoop - the elephant in the room -- Databases -- Hadoop Spark-ed up -- R - The unsung Big Data hero -- Summary -- Chapter 2: Introduction to R Programming Language and Statistical Environment -- Learning R -- Revisiting R basics -- Getting R and RStudio ready -- Setting the URLs to R repositories -- R data structures -- Vectors -- Scalars -- Matrices -- Arrays -- Data frames -- Lists -- Exporting R data objects -- Applied data science with R -- Importing data from different formats -- Exploratory Data Analysis -- Data aggregations and contingency tables -- Hypothesis testing and statistical inference -- Tests of differences -- Independent t-test example (with power and effect size estimates) -- ANOVA example -- Tests of relationships -- An example of Pearson's r correlations -- Multiple regression example -- Data visualization packages -- Summary -- Chapter 3: Unleashing the Power of R from Within -- Traditional limitations of R -- Out-of-memory data -- Processing speed -- To the memory limits and beyond -- Data transformations and aggregations with the ff and ffbase packages -- Generalized linear models with the ff and ffbase packages -- Logistic regression example with ffbase and biglm -- Expanding memory with the bigmemory package -- Parallel R -- From bigmemory to faster computations -- An apply() example with the big.matrix object -- A for() loop example with the ffdf object -- Using apply() and for() loop examples on a data.frame -- A parallel package example -- A foreach package example -- The future of parallel processing in R -- Utilizing Graphics Processing Units with R.…”
Libro electrónico