Reading List

.NET integration for ReactJS

The library for web and native user interfaces

This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with GitHub, and reproducible document preparation with R markdown.

A general introduction to Raku

Clear examples in R. Purpose of this book; Specific learning goals; Pre-requisites; What this book will not cover

Welcome | Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data.

Learn how to create a package, the fundamental unit of shareable, reusable, and reproducible R code.

This book, written by Protesilaos Stavrou, also known as ‘Prot’, provides a big picture view of the Emacs Lisp programming language.

Learn how to build a good looking responsive website supporting lightbox images, formulae, google prettify code fragments within a Gerstner grid