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  1. Effective Data Wrangling and Exploration with R

    Data wrangling is one of the most important steps in data science and analytics, for it is claimed that it takes between 80% to 90% of an analyst’s time. Data wrangling goes by many names including data munging, data manipulation, data preparation and data transformations. This book is all about data wrangling and exploration with R.

  2. Behavior Analysis with Machine Learning and R
    Behavior Analysis with Machine Learning and R
    A Sensors and Data Driven Approach
    Enrique Garcia Ceja

    Learn how to leverage the power of machine learning and deep learning to analyze behavioral patterns from sensors data and electronic records. This book shows you how to explore, preprocess, encode, and visualize your data. Learn introductory machine learning concepts and how to train supervised and unsupervised models using R.

  3. Data Science con R (Spanish version)
    Data Science con R (Spanish version)
    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.

  4. Computing Matrix Algebra
    Computing Matrix Algebra
    practical notes foR data science
    Mario De Toma

    This book is actually a cheat sheet about computing matrix algebra operations such as matrix multiplication, inversion and factorization.It is written foR (aspiring) data scientists where with "foR" (capital letter R) I mean the side of data science addicted to R and its gorgeous ecosystem especially including Rcpp, RcppArmadillo and RcppEigen.

  5. Data Science - Regression Analysis (DIY for newbies)
    Data Science - Regression Analysis (DIY for newbies)
    Includes 100 solved problems
    Geetha Subramanian

    This book contains detailed stepwise solutions to Regression problems for beginners. It is a collection of solutions in Python and R programming language.

  6. Python Command Line Tools
    Python Command Line Tools
    Design powerful apps with Click
    Noah Gift and Alfredo Deza

    Learn the ultimate interface...the command-line.

  7. Introducción al Análisis Exploratorio de Datos.
    Introducción al Análisis Exploratorio de Datos.
    Aplicaciones con R y datos reales.
    Vicente Coll-Serrano

    En el manual expongo, de forma clara y sencilla, los conceptos básicos de un análisis exploratorio de datos a nivel descriptivo y cómo llevarlo a la práctica con el software estadístico R y datos reales. El libro está pensado para que el lector avance paso a paso en su proceso de auto-aprendizaje, por lo que se proporcionan muchos ejemplos.

  8. Modern R with the tidyverse
    Modern R with the tidyverse
    Bruno Rodrigues, Phd

    Learn to use R, the tidyverse collection of packages and functional programming concepts to write efficient and readable code.

  9. Sharing your work
    Sharing your work
    An open source toolchain for creating and sharing data products.
    Martin Frigaard

    A primer on RStudio, Git, and GitHub.

  10. ggplot2 in 2
    ggplot2 in 2
    Learn the ggplot2 R package in two hours
    Lucy D'Agostino McGowan

    Learn ggplot2 in two hours!

  11. Introduktion til R
    Introduktion til R
    Tue Hellstern

    Denne bog giver dig en introduktion til programmeringssproget R

  12. How To Develop A Leanpub Course With R
    How To Develop A Leanpub Course With R
    Shannon Ellis and John Muschelli

    Interested in developing Leanpub Courses the way we did for our Chromebook Data Science Course Set? This book will walk you through the necessary steps to streamline content development using our workflow in R.

  13. Daily Fantasy Sports with R
    Daily Fantasy Sports with R
    Building an NBA Projection System
    Robert Zamora

    Data analysis is the process of converting data into useful information. This book introduces data analysis applied to NBA daily fantasy sports (DFS) using the R programming language. You will learn how to wrangle and visualize data, build and test prediction models, and collect and import data from web-based sources.

  14. The Dynamics of Infectious Diseases
    The Dynamics of Infectious Diseases
    Modelling Epidemiology with R
    Jacob Koella

    Understanding the dynamics of epidemiology is indispensable to control infectious diseases. The Dynamics of Infectious Diseases will help you to get a grasp of the fundamentals, and it will show you how to use and develop these aspects with the programming language R.

  15. Mixed and Phylogenetic Models: A Conceptual Introduction to Correlated Data

    Are you confident your statistical results are correct? To answer this, you need to know the concepts behind statistics. This book, and R code, focus on data with correlated errors that arise in mixed models and phylogenetic models. It will hopefully give you confidence to judge statistical methods and the results they produce. The book is free!