Your Guide to Quality Data Science Products

Appsilon’s open source shiny.info package just received a major update and is now available on CRAN. A great solution for development and testing, shiny.info allows for displaying diagnostic information from inside Shiny apps.

Artificial Intelligence, Machine Learning, and Deep Learning models have demonstrated significant power to grow and improve businesses. This article explains how to properly approach developing an AI model.

As part of our D4G Initiative and with the support of a Google grant, Appsilon Data Science will be contributing to to the work of biodiversity conservationists at the National Parks Agency in Gabon in collaboration with the University of Stirling.

Can you build Shiny apps without any R knowledge? This R Shiny Dashboard Tutorial shows you my experience with learning R creating R Shiny dashboards in 2 days.

Satellite image datasets are now readily accessible for use in Data Science and Machine Learning projects. This article will explain how to acquire these datasets and what you can do with them.

Have you considered adding AI/ML to your organization's operations? AI models can significantly reduce costs when they are implemented properly, but can end up in "purgatory" with the wrong approach. Here's how to properly implement AI models.

We'll show you how to import the proper libraries, set up a dashboard, add UI components, and more!

Appsilon engineers Paweł and Pedro share their perspective on rstudio::conf 2020, especially news and updates about R packages...

RStudio::conf 2020 is a wrap!

We recently took part in Hakuna-ma Data, a competition organised by DrivenData in partnership with Microsoft’s AI for Earth, which asked participants to build an algorithm for wildlife detection that would generalise well across time and locations...

rstudio::conf 2020 is here! Appsilon Data Science is proud to be a co-sponsor of the conference. Here is some information about the presentations we are doing and others that we hope to attend.

"So we sat down with the project manager on the client side, re-ordered the priorities, estimated additional work and were able to start coding on the very same day."