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Drugs not bugs: effective use of R in pharma
Eye candy: surprising and delightful uses of R
It takes a village: building communities of practice
Rapidly responding to world events with R
What they forgot to teach you about your career
Working with people is hard
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Generating high quality data
Just typing R code: advanced R programming
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Unexpected uses of R
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Cat herding: solving big problems by bringing people together
Quarto deep dive
RMarkdown and Quarto
Some of my best friends use Python
Take a sad process and make it better: project and process makeovers
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Data science in production
I like big apps: shiny apps that scale
Machine learning
Pour some glitter on it: polishing the design of your shiny apps
Updates from the tidymodels team
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Welcome Reception
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Good practices for applied machine learning - from model development to model deployment
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The Past and Future of Shiny
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Quarto for the Curious
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Evening Dinner & Activities
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Making Data Pipelines in R: A Story From A “Self-Taught” Perspective
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R, Python, and Tableau: A Love Triangle
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R Markdown + RStudio Connect + R Shiny: A Recipe for Automated Data Processing, Error Logging, and Process Monitoring
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Demystifying MLOps
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tidyclust - expanding tidymodels to clustering
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Project Immortality: Using GitHub To Make Your Work Live Forever
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Highlights of the knitr package from the past two years
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Garbage Data, And What To Do About Them
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censored - Survival Analysis in tidymodels
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dbcooper: Turn any database into an R or Python package
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The R integration in Power BI: Why R developers should be Interested
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Do It For Yourself: Creating a data input platform using R
#24
Scaling and automating R workflows with Kubernetes and Airflow
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R Shiny - From Conception to the Cloud
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Packages and Process
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Robust R Deployments: Building a Pipeline from RStudio to Production
#28
Sometimes you just need words
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Hello Quarto: Share • Collaborate • Teach • Reimagine
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A new way to build your Shiny app's UI
#31
Running Shiny without a server
#32
Data science training in communities with limited technology resources and opportunities
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An introduction to R7
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You should be using renv
#35
Designing for people is hard
#36
Exploratory Spatial Data Analysis in the tidyverse
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The Future of missing data
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These are a few of my favorite things (about Quarto presentations)
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Making awesome automations with GitHub Actions
#40
Dashboard-Builder: Building Shiny Apps without writing any code
#41
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It's about time
#44
Creating a Design System for Shiny and RMarkdown
#45
Visualizing distributions and uncertainty using ggdist
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leafdown: Interactive multi-layer maps in Shiny apps
#47
Building a ggplot2 rollercoaster: Creating amazing 3D data visualizations in R
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{shinytest2}: Regression testing for Shiny applications
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Achieving a seamless workflow between R, Python and SAS from within RStudio
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Zero-setup R workshops with GitHub Codespaces
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