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Keynote
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Track Cherry Blossom
All
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
Track National Harbor 10+11
All
Databases
Generating high quality data
Just typing R code: advanced R programming
Teaching data science
Unexpected uses of R
Working with code is hard
Track Potomac C
All
Business intelligence
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
Track Potomac D
All
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
Workshop
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Ania Tassinari
Servier Pharmaceuticals
Data Scientist
Monday
, July 25
7:30am EDT
Breakfast
5. Maryland
9:00am EDT
Building Production-Quality Shiny Applications
National Harbor 2
11:00am EDT
Building Production-Quality Shiny Applications
National Harbor 2
12:30pm EDT
Lunch
5. Maryland
1:30pm EDT
Building Production-Quality Shiny Applications
National Harbor 2
3:30pm EDT
Building Production-Quality Shiny Applications
National Harbor 2
5:30pm EDT
Book Signing Reception
3. Cherry Blossom
Tuesday
, July 26
7:30am EDT
Breakfast
5. Maryland
9:00am EDT
Building Production-Quality Shiny Applications
National Harbor 2
11:00am EDT
Building Production-Quality Shiny Applications
National Harbor 2
12:30pm EDT
Lunch
5. Maryland
1:30pm EDT
Building Production-Quality Shiny Applications
National Harbor 2
3:30pm EDT
Building Production-Quality Shiny Applications
National Harbor 2
5:30pm EDT
Welcome Reception
6. Riverview Ballroom
Wednesday
, July 27
7:30am EDT
Breakfast
5. Maryland
9:00am EDT
Good practices for applied machine learning - from model development to model deployment
0. Potomac A+B
11:00am EDT
R Package Assessment: Lessons from Pharma
3. Cherry Blossom
censored - Survival Analysis in tidymodels
2. Potomac D
11:20am EDT
tidyclust - expanding tidymodels to clustering
2. Potomac D
11:40am EDT
Demystifying MLOps
2. Potomac D
12:00pm EDT
Lunch
5. Maryland
Pharma / Life Sciences - Birds of a Feather
Maryland 1, 2, & 3
1:30pm EDT
Making Data Pipelines in R: A Story From A “Self-Taught” Perspective
4. National Harbor 10+11
Do It For Yourself: Creating a data input platform using R
1. Potomac C
Remote Content Execution with RStudio Connect and Kubernetes
2. Potomac D
1:50pm EDT
Garbage Data, And What To Do About Them
4. National Harbor 10+11
Oddly Satisfying - Find delight in the mundane
1. Potomac C
Data science in your customers hands on a budget and a deadline: Publishing Customer Facing Products with RStudio Connect
2. Potomac D
2:10pm EDT
An Integrated Workflow: Microsoft Azure DevOps, RStudio Workbench, RStudio Connect
3. Cherry Blossom
Project Immortality: Using GitHub To Make Your Work Live Forever
4. National Harbor 10+11
Advocating for Automation: Adapting Current Tools in Environmental Science through R
1. Potomac C
2:30pm EDT
R Markdown + RStudio Connect + R Shiny: A Recipe for Automated Data Processing, Error Logging, and Process Monitoring
4. National Harbor 10+11
3:20pm EDT
Quarto for the Curious
1. Potomac C
3:40pm EDT
Sometimes you just need words
1. Potomac C
4:30pm EDT
The Past and Future of Shiny
0. Potomac A+B
5:30pm EDT
Birds of a Feather Happy Hour - Industry Groups
Chesapeake
6:00pm EDT
Evening Dinner & Activities
7. Orchard Terrace
Thursday
, July 28
7:30am EDT
Breakfast
5. Maryland
9:00am EDT
Hello Quarto: Share • Collaborate • Teach • Reimagine
0. Potomac A+B
10:30am EDT
The Benefit of Talking to the "Non-Datas"
3. Cherry Blossom
10:50am EDT
Achieving a seamless workflow between R, Python and SAS from within RStudio
1. Potomac C
11:00am EDT
Making awesome automations with GitHub Actions
2. Potomac D
11:30am EDT
Comparing package versions with Diffify
2. Potomac D
11:35am EDT
Visualizing distributions and uncertainty using ggdist
2. Potomac D
11:40am EDT
The Future of missing data
2. Potomac D
12:00pm EDT
Lunch
5. Maryland
1:30pm EDT
A new way to build your Shiny app's UI
2. Potomac D
1:50pm EDT
Demystifying the art of creating custom libraries for your organization
4. National Harbor 10+11
2:10pm EDT
You should be using renv
4. National Harbor 10+11
Creating a Design System for Shiny and RMarkdown
2. Potomac D
2:30pm EDT
Save an ocean of time: streamline data wrangling with R
1. Potomac C
Dashboard-Builder: Building Shiny Apps without writing any code
2. Potomac D
3:40pm EDT
From summarizing projects to setting tags, uses of parsing R files
4. National Harbor 10+11
4:00pm EDT
An introduction to R7
4. National Harbor 10+11
4:30pm EDT
Data science training in communities with limited technology resources and opportunities
0. Potomac A+B
5:30pm EDT
R-Ladies Reception
Maryland 1, 2, & 3
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rstudio::conf(2022)
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rstudio::conf(2022)
Jul 25
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28, 2022
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, July 28
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Gaylord National, Forest Heights, MD, USA
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0. Potomac A+B
1. Potomac C
2. Potomac D
3. Cherry Blossom
4. National Harbor 10+11
5. Maryland
6. Riverview Ballroom
7. Orchard Terrace
Chesapeake
Chesapeake 4+5+6
Chesapeake 9
Chesapeake D
Chesapeake E
Chesapeake F
Chesapeake G+H+I
Maryland 1
Maryland 1, 2, & 3
Maryland 2
Maryland 3
Maryland 4+5
Maryland 4, 5, & 6
Maryland 6
National Harbor 12+13
National Harbor 2
National Harbor 3
National Harbor 4+5
National Harbor 6+7
Filter By Type
Keynote
Meal
Social
Track Cherry Blossom
All
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
Track National Harbor 10+11
All
Databases
Generating high quality data
Just typing R code: advanced R programming
Teaching data science
Unexpected uses of R
Working with code is hard
Track Potomac C
All
Business intelligence
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
Track Potomac D
All
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
Workshop
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