Reactive programming is shaping the future of how we model data. With reactive, not only can you concisely wrangle and analyze static data, you can effectively work with data as a real-time infinite feed. Reactive Extensions (Rx) first gained traction in 2009 and has been ported to over a dozen major languages and platforms.
Refine your data science skills with the heavy armory of tools provided by Julia
The R programming language has arguably become the single most important tool for computational statistics, visualization, and data science. With this Learning Path, master the basics that you'll need as a data scientist. You'll work your data like never before.
Unleash the powerful capabilities of R to work effectively with data.
Over 100 hands-on tasks to help you effectively solve real-world data problems using the most popular R packages and techniques