See Appsilon Presentations on Computer Vision and Scaling Shiny at Why R? 2020

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Mark your calendars! Join Appsilon at the Why R? Conference on Thursday, November 12th @ 8PM UTC+1 / 2PM EST for two talks by Appsilonians. We will discuss wildlife preservation with computer vision and scaling Shiny apps on a budget. You can find the meetup link here and a direct link to the presentations on YouTube here.

Preserving Wildlife with Computer Vision

Appsilon Senior Data Scientist Jędrzej Świeżewski, PhD will discuss how Appsilon has managed to assist wildlife conservationists in their efforts in central Africa using computer vision. He will touch on the modeling, real-life implementation, and will also share a treat for R lovers. If you’re interested in the intersection of R and computer vision, see a previous talk by Jędrzej about how to make a computer vision model within an R environment here.

Scaling Shiny Dashboards on a Budget

Appsilon Infrastructure Engineer Damian Budelewski will show you how to prepare your Shiny dashboard for a high traffic load. He will also help you understand the costs and requirements of hosting Shiny apps in the cloud. He will illustrate by showing you an example of a Shiny app deployed on Shiny Server Open Source and hosted on AWS. To learn more about alternative approaches to scaling Shiny, go here.

Vote for the People’s Choice Award in Appsilon’s 2020 shiny.semantic PoContest! Vote here until Friday, November 10th.

Appsilon is Hiring

Appsilon is currently hiring for multiple open roles, including Senior External R Shiny Developers, a Frontend Engineer, a Senior Infrastructure Engineer, a Project Manager, and a Community Manager. Appsilon is a fully remote company with team members in Europe, the UK, Africa, and South America. We are global leaders in R Shiny seeking top talent to work with us in a highly collaborative and creative environment.

Appsilon Hiring

Article See Appsilon Presentations on Computer Vision and Scaling Shiny at Why R? 2020 comes from Appsilon | End­ to­ End Data Science Solutions.

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