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Data Science con R

Análisis de Datos y algoritmos de predicción con R

Daniel Paredes Inilupu

Descubre cómo aprender a ser un Data Scientist a tu propio ritmo con contenido actualizado y con ejemplos de Latinoamérica. Desde análisis de datos hasta algoritmos predicción con machine learning. Con la compra del libro accedes a las 2 versión disponibles: pdf y web y a más de 100 ejercicios incluidos.

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About

About

About the Book

Aprender a tomar decisiones en base a la data es hoy en día un requisito transversal entre industrias. En este libro encontrarán desde aspectos básicos del análisis de datos, así como visualización, teoría de probabilidades, inferencias, modelado y machine learning. El contenido está adaptado al mercado hispanohablante como incentivo de brindar oportunidades a nuevos talentos que quieran formarse como Data Scientists.

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Data ScienceRSystems Engineering

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Creative Commons Attribution-ShareAlike 4.0 International License

Author

About the Author

Daniel Paredes Inilupu

MBA from London Business School. System Engineer from Universidad Nacional de Ingeniería, Perú.

Contents

Table of Contents

Parte I: Fundamentos de R

Capítulo 1: Introducción a objetos

Capítulo 2: Manipulación de data frames

Parte II: Visualización y resumen de datos

Capítulo 3: Ggplot y dplyr

Capítulo 4: Gapminder

Parte III: Estadística

Capítulo 5: Probabilidades discretas

Capítulo 6: Probabilidades continuas

Capítulo 7: Inferencias

Parte IV: Data Wrangling

Captíulo 8: Importación y ordenamiento de datos

Capítulo 9: Procesamiento de cadenas y Minería de texto

Parte V: Machine Learning

Capítulo 10: Aprendizaje no supervisado

Capítulo 11: Aprendizaje supervisado

Parte VI: Casos reales

Capítulo 12: ¿Cómo ganar dinero con Finsmart?

Capítulo 13: Google Analytics desde R

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