Site icon R-bloggers

2020 Earl Conference Insights

[This article was first published on RBlog – Mango Solutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

This year the EARL conference was held virtually due to the restrictions imposed by COVID-19. Although this removed the valuable networking element of the conference, the ‘VirtuEARL’ virtual approach meant we reached a geographically wider audience and ensured a successful conference. Thought leadership from academia and industry logged in to discover how R can be used in business, and over 300 data science professionals convened to join workshops or hear presenters share their novel and interesting applications of R. The flexibility of scheduling allowed talks to be picked according to personal or team interests.

The conference kicked off with workshops delivered by Mango data scientists and guest presenters, Max Kuhn of RStudio and Colin Fay from ThinkR, with topics including data visualisation, text analysis and modelling. The presentation day both began and finished with keynote presentations: Annarita Roscino from Zurich spoke about her journey from data practitioner to data & analytics leader – sharing key insights from her role as a Head of Predictive Analytics, and Max Kuhn from RStudio used his keynote to introduce tidymodels – a collection of packages for modelling and machine learning using tidyverse principles.

Between these great keynotes, EARL offered a further 11 presentations from across a range of industry sectors and topics. A snapshot of these shows just some of the ways that R is being used commercially: Eryk Walczak from the Bank of England revealed his use of text analysis in R to study financial regulations, Joe Fallon and Gavin Thompson from HMRC presented on their impressive work behind the Self Employment Income Support Scheme launched by the Government in response to the Covid-19 outbreak, Dr. Lisa Clarke from Virgin Media gave an insightful and inspiring talk on how to maximize an analytics team’s productivity, whilst Dave Goody, lead data scientist from the Department of Education, presented on using R shiny apps at scale across a team of 100 to drive operational decision making.

Long time EARL friend and aficionado, Jeremy Horne of DataCove, demonstrated how to build an engaging marketing campaign using R, and Dr Adriana De Palma from the Natural History Museum showed her use of R to predict biodiversity loss.

Charity donation (awaiting confirmation)

Due to the reduced overheads of delivering the conference remotely this year, the Mango team decided to donate the profits of the 2020 EARL conference to Data for Black Lives. This is a great non-profit organization dedicated to using data science to create concrete and measurable improvements to the lives of Black people. They aim to use data science to fight bias, promote civic engagement and build progressive movements. The pledge has been made and details of the donation will be announced shortly

Whilst EARL 2020 was our first such virtual event, the conference was highly successful. Attendees described it as an “unintimidating and friendly conference,” with “high quality presentations from experts in their respective fields” and were delighted to see how R and data science in general were being used commercially. One attendee best described the conference: “EARL goes beyond introducing new packages and educates attendees on how R is being used around the world to make difficult decisions”.

If you’d like to learn more about EARL 2020 or see the conference presentations in full , click here.

The post 2020 Earl Conference Insights appeared first on Mango Solutions.

To leave a comment for the author, please follow the link and comment on their blog: RBlog – Mango Solutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.