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Category: "R"

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  1. Bioconductor
    Bioconductor
    An Introduction to Core Technologies
    Kasper D. Hansen

    The Bioconductor project is a widely used open source and open development platform for software for computational biology. It is a leading platform for doing data science in Genomics.  This book covers the core functionality needed to deploy Bioconductor on modern datasets, and will lay the foundation for you to learn and explore parts of the project devoted to specific application domains.

  2. Cricket analytics with cricketr
    Cricket analytics with cricketr
    Analysis of performances of cricketrs with R package cricketr
    Tinniam V Ganesh

    This book includes detailed analyses of cricket performances of top cricket players in the world based on ESPN Cricinfo Statsguru. An R package cricketr (which I authored), now in CRAN, was used for this analysis for Test, ODI and Twenty20 cricket. The book contains details on how to use R package cricketr for analysis of other players

  3. My test book_178
    My test book_178
    Analysis
    Tinniam V Ganesh
    No Description Available
  4. Introduction to Econometric Production Analysis with R
    Introduction to Econometric Production Analysis with R
    Seventh Draft Version
    Arne Henningsen

    This book gives an introduction to several aspects of econometric production analysis. It provides many practical examples using the R statistical software.

  5. Wrangling F1 Data With R
    Wrangling F1 Data With R
    A Data Junkie's Guide
    Tony Hirst

    The data's out there, but what can we do with it? As the ultimate chaser of technological innovation, Formula One motor sport is still outpaced by baseball and cricket in the stats fans stakes. But no more: it's time for the F1 data junkies to fight back...

  6. Practical Machine Learning in R
    Practical Machine Learning in R
    Kyriakos Chatzidimitriou, Themistoklis Diamantopoulos, Thomas Karanikiotis, Michail Papamichail, and Andreas Symeonidis

    Do you want to start using R for crunching machine learning models right from the start with examples? Then this book is for you.