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New York R Conference 2020

New York R Conference 2020

12 - April 15, 2020

Discover the 25 talks of this edition.

Dr. Rob J. Hyndman - Ensemble Forecasts with {fable}
Dr. Adam Obeng - Adaptive Experimentation
Ludmila Janda - Using R to Better Understand R-Ladies NYC
Emily Robinson - {funneljoin}: Defining a Tidy Grammar on Funnels in R
Jared P. Lander - Finding the Tallest Tree: Comparing Decision Tree, Random Forest & Boosted Tree
Dan Chen - Grading Code with gradethis
Dr. Jon Krohn - Deep Learning Battle: TensorFlow 2 vs PyTorch
Andrew Gelman - Truly Open Science: From Design and Data Collection to Analysis and Decision Making
David Smith - MLOps with R: An End-to-End Process for Building Machine Learning Applications
Laura Gabrysiak - Re-Inventing Customer Engagement with Machine Learning
Brooke Watson Madubuonwu - Modeling COVID-19 Spread in Jails and Communities, in R
Dr. Sebastian Teran Hidalgo - Doubly Robust Estimation of Causal Effects in R
Catherine Zhou - Why NYR? Finding You(R) Community
Dr. Jacqueline Nolis - What I Learned from Porting my Viral Website from .NET to {shiny}
Sonia Ang - Automated Machine Learning
Emily Dodwell - All the World’s A Stage: Elements for Vis of Multivariate Spatiotemporal Data in R
Jonah Gabry - A New Way to Interface with Stan from R
Wes McKinney and Dr. Neal Richardson - Speeding Up Data Access in R with Apache Arrow
Dr. Thomas Mock - Higher, Further, Faster with Marvelous RMarkdown
David Robinson - The {widyr} Package
Dr. Max Kuhn - Resampling, Repeated Measures Designs, and You
Dr. Erin LeDell - Scalable Automatic Machine Learning in R
Monica Thieu - How to Prepare and Teach an R Lesson
Camelia Hssaine - What to do When You Can't A/B test: Exploring Different Causal Inference Methods
BONUS TALK | Heather Nolis - Speech: The Other, Other NLP

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New York R Conference 2020