
The Essentials of Data Science: Knowledge Discovery Using R by Graham J Williams
The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data.
Building on over thirty years’ experience in teaching and practising data science, the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets.
The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data, the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.
-
Advanced R
-
Using R for Introductory Statistics
-
Introduction to Scientific Programming and Simulation Using R
-
Reproducible Research with R and R Studio
-
Mastering data.table in R
-
Testing R Code
-
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
-
Analyzing Baseball Data with R
-
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
-
R and MATLAB
-
Growth Curve Analysis and Visualization Using R
-
Dose-Response Analysis Using R
-
Spatial Analysis in Geology Using R
-
Using the R Commander
-
Behavior Analysis with Machine Learning Using R
-
blogdown
-
Javascript for R
-
Using R for Modelling and Quantitative Methods in Fisheries
-
Distributions for Modeling Location, Scale, and Shape
-
Introduction to Political Analysis in R
-
Introductory Fisheries Analyses with R
-
Basics of Matrix Algebra for Statistics with R
-
Implementing Reproducible Research
-
R Graphics
-
Modeling Data with Functional Programming in R, Volume 1
-
Statistical Genetics
"I have several books on data science and R, as well as other similar subjects and programming languages, in my personal libraryHowever, this book is a great blend of important data science topics and R programming that will make it a great reference for anyone working in this important and immensely popular area. I highly recommend this book for college students learning what it takes to start their career in data science or even current professionals wanting to make a career change or who just want to know more about the subject (and do some R programming as well)."
~Dean V. Neubauer, Techometrics
"Due to the self-contained introduction to many of the features of R and RStudio, Graham J. Williams The Essentials of Data Science, Knowledge Discovery Using R would make an excellent recommended or supplementary text for a course that plans to use the rattle package. This book would also serve as a great resource for those with an interest in data science who would like a hands-on approach to learning R and gettting a flavor for a handful of topics within data science."
~Katherine M. Kinnaird, Brown University
| SKU | Unavailable |
| ISBN 13 | 9781498740005 |
| ISBN 10 | 1498740006 |
| Title | The Essentials of Data Science: Knowledge Discovery Using R |
| Author | Graham J Williams |
| Series | Chapman And Hall Crc: The R Series |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Inc |
| Year published | 2017-07-13 |
| Number of pages | 344 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |

























