Links to slides from rstudio::conf 2019
Links to slides to talks at the 2019 rstudio::conf
Schedule: https://www.rstudio.com/conference/#speakers
Pull requests welcome! Or add an issue, or tweet @kwbroman or email Karl Broman.
Workshops material
- Applied Machine Learning
- Big Data with R
- Data Science in the Tidyverse
- Deep learning with R (Tensorflow) day 1 and day 2
- Introduction to Shiny and R Markdown workshop
- Shiny in Production
- Train-the-trainer workshop
- What they forgot to teach you about R
Wednesday 2019-01-16 ePosters
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Alex Gold, @alexkgold, Upgrading to R: Tips and mistakes you don't have to make
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Leonard Kiefer, @lenkiefer, Using R to Analyze Economic and Housing Market Trends
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Ted Laderas, @tladeras, and Jessica Minnier, @datapointier Democratizing data science using Shiny and LearnR
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Nick Strayer, @nicholasstrayer Multimorbidity explorer: A shiny app for exploring EHR and biobank data
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Jeremy Wildfire, @jwildfire, Modernizing the clinical trial analysis pipeline with R and JavaScript
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Hiroaki Yutani @yutannihilat_en, Introduction to gghighlight
Thursday 2019-01-17
9:30 Keynote
11:00 Session 1, Track 1: Tidyverse
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Karthik Ram, @_inundata, rOpenSci, A guide to modern reproducible data science with R
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Jeffrey Arnold, @jrnold, Insight, Solving R for data science (solutions to R4DS exercises)
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Kara Woo, @kara_woo, Sage Bionetworks, Box plots: A case study in debugging and perseverance (the PR of interest)
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Amelia McNamara, @AmeliaMN, University of St. Thomas, Working with categorical data in R without losing your mind (related paper from the DSS collection)
11:00 Session 1, Track 2: Interop
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Wes McKinney, RStudio, Ursa Labs and Apache Arrow in 2019
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Jonathan McPherson, @jmcphers, RStudio, New language features in RStudio 1.2, (example code and data)
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Edgar Ruiz, RStudio, Databases using R: The latest
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Kelly O’Briant, @kellrstats, RStudio, Configuration management tools for the R admin
11:00 Session 1, Track 3: Production
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Heather & Jacqueline Nolis, @heatherklus and @skyetetra, Nolis, LLC, Push straight to prod: API development with R and Tensorflow at T-Mobile
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Mark Sellors, Mango Solutions, R in production
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Jeff Allen, RStudio, RStudio Connect: Past, present, and future
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Sean Lopp, RStudio, Announcing RStudio Package Manager
2:00 Session 2, Track 1: Teaching
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Jesse Mostipak, @kierisi, Teaching Trust, R4DS online learning community: Improvements to self-taught data science & the critical need for diversity, equity, and inclusion in data science education
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Irene Steves, @i_steves, Teaching data science with puzzles
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Kelly Nicole Bodwin, @kellybodwin, California Polytechnic State University, Introductory statistics with R: Easing the transition to software for beginner students (github repo)
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Tracy Teal, @tracykteal, The Carpentries, Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops
2:00 Session 2, Track 2: Distributed
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Darby Hadley, RStudio, RStudio Job Launcher: Changing where we run R stuff
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Javier Luraschi, @javierluraschi, RStudio, Scaling R with Spark
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Kevin Kuo, RStudio, Introducing mlflow
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James Blair, @blair09m, RStudio, Democratizing R with Plumber APIs
2:00 Session 2, Track 3: Industry
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Brooke Watson, @brookLYNevery1, ACLU, R at the ACLU: Joining tables to reunite families
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Emily Robinson, @robinson_es, Data Scientist at DataCamp, Building an A/B testing analytics system with R and Shiny
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Nic Crane, @nic_crane, Elucidata, The future’s Shiny: Pioneering genomic medicine in R
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Joe Rickert, @rstudiojoe, RStudio, R Consortium initiatives in medicine
4:00 Session 3, Track 1: Tidyverse
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Earo Wang, @earowang, Monash University, Melt the clock: Tidy time series analysis
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Tyler Morgan-Wall, @tylermorganwall, Institute for Defense Analyses, 3D mapping, plotting, and printing with rayshader
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Edzer Pebesma, @edzerpebesma & Michael Sumner, Etienne Racine, Institute for Geoinformatics, University of Muenster, Germany, Spatial data science in the Tidyverse
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Thomas Lin Pedersen, @thomasp85, RStudio, gganimate live cookbook
4:00 Session 3, Track 2: Modeling
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Alex Hayes, @alexpghayes, University of Wisconsin, Madison, Solving the model representation problem with broom
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Sigrid Keydana, @zkajdan, RStudio, Why TensorFlow eager execution matters
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Max Kuhn, @topepos, RStudio, parsnip: A tidy model interface
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Claus Wilke, @clauswilke, The University of Texas at Austin, Visualizing uncertainty with hypothetical outcomes plots
4:00 Session 3, Track 3: Kaleidoscope
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Matt Dancho, @mdancho84, Business Science, Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition
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Hao Zhu, @haozhu233, Hebrew SeniorLife – Institute for Aging Research, Empowering a data team with RStudio addins (example/demo)
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Karl Broman, @kwbroman, University of Wisconsin, R/qtl2: Rewrite of a very old R package
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Amanda Gadrow, @ajmcoqui, RStudio, Getting it right: Writing reliable and maintainable R code
Friday 2019-01-18
9:00 Keynote
- Felienne, @felienne, LIACS - Universiteit Leiden, Explicit direct instruction in programming education
10:30 Session 4, Track 1: org-thinking
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James (JD) Long, @CMastication, Renaissance Re, Putting empathy in action: Building a `community of practice' for analytics in a global corporation
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Tonya Filz, @TonyaFilz, RStudio, The resilient R champion
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Hilary Parker, @hspter, Stitch Fix, Cultivating creativity in data work
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Angela Bassa, @AngeBassa, iRobot, Data science as a team sport
10:30 Session 4, Track 2: programming
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Gabor Csardi, @GaborCsardi, RStudio, pkgman: A fresh approach to package installation
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Jim Hester, @jimhester_, RStudio, It depends: A dialog about dependencies
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Jeroen Ooms, @opencpu, rOpenSci, A preview of Rtools 4.0
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Miles McBain, @MilesMcBain, ACEMS, Queensland University of Technology, Our colour of magic: The open sourcery of fantastic R packages
10:30 Session 4, Track 3: publication
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Garrett Grolemund, @StatGarrett, RStudio, R Markdown: The bigger picture
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Yihui Xie, @xieyihui, RStudio, pagedown: Creating beautiful PDFs with R Markdown and CSS (pagedown github repo)
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Rich Iannone, @riannone, RStudio, Introducing the gt package
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Mike K Smith, @MikeKSmith, Pfizer Ltd, The lazy and easily distracted report writer: Using rmarkdown and parameterized reports
1:00 Session 5, Track 1: teaching
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Caitlin Hudon, @beeonaposy, R-Ladies Austin, Learning from eight years of data science mistakes
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Mary Rudis, @mrshrbrmstr, Penn State Harrisburg, Catching the R wave: How R and RStudio are revolutionizing statistics education in community colleges (and beyond)
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Carl Howe, @cdhowe, RStudio, The next million R users
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Mel Gregory, RStudio, RStudio Cloud for education
1:00 Session 5, Track 2: programming
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Hadley Wickham, @hadleywickham, RStudio, vctrs: Tools for making size and type consistent functions
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Jenny Bryan, @jennybryan, RStudio, Tidy eval in context
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Lionel Henry, @_lionelhenry, RStudio, Working with names and expressions in your tidy eval code
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Jesse Sadler, @vivalosburros, independent researcher, Learning and using the tidyverse for historical research
1:00 Session 5, Track 3: shiny
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Eric Nantz, @thercast, Eli Lilly, Effective use of Shiny modules in application development
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Barret Schloerke, @schloerke, RStudio, Reactlog 2.0: Debugging the state of Shiny
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Alan Dipert, @alandipert, RStudio, Integrating React.js and Shiny
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Ian Fellows, Fellows Statistics, Don't let long running tasks hang your users: introducing ipc for Shiny