Talks from our 2018 conference in San Diego, CA
Machine Learning with R and TensorFlow
In this talk we’ll explore the use of TensorFlow from R, describing the complete workflow including data ingestion, training, and deploying models into production.
To the Tidyverse and Beyond – Dianne Cook
What are the future challenges for Data Science?
R for Presidents – Tareef Kawaf
How does an executive use R to run their business?
Scaling Shiny apps with async programming – Joe Cheng
Asynchronous programming offers a way to offload certain classes of long-running operations from the main R thread, such that Shiny apps can remain responsive.
Fireside Chat: R In Industry Discussion
Fireside Chat: Tidyverse Discussion
Differentiating by data science – Eric Colson
Storytelling with R – Olga Pierce
Imagine Boston 2030: Using R-Shiny to keep ourselves accountable and empower the public – Kayla Patel
Agile data science – Elaine McVey
Teach the Tidyverse to beginners - David Robinson
How I Learned to Stop Worrying and Love the Firewall – Ian Lyttle
Achieving impact with advanced analytics: Breaking down the adoption barrier – Aaron Horowitz
A SAS-to-R success story – Elizabeth J. Atkinson
The R Admin is rad: A guide to professional R tooling and integration
Sharing analysis results with RStudio Connect – Jeff Allen
Parameterized R Markdown reports with RStudio Connect – Aron Atkins
Drill-down reporting with Shiny – Bárbara Borges Ribeiro
Reinforcement learning in Minecraft with CNTK-R – Ali-Kazim Zaidi
Large scale machine learning using TensorFlow, BigQuery and CloudML Engine within RStudio – Michael Quinn