The only end-to-end data + AI observability platform for enterprise teams.

By Jeremy Keith

This book covers the use of Redis. It was originally written by Salvatore Sanfilippo, and has been updated through the open source process.

.NET integration for ReactJS

The library for web and native user interfaces

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

A general introduction to Raku

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.

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.