rstudio::conf 2020

Talks from our 2020 conference in San Francisco, CA

  • Open Source Software for Data Science - J.J. Allaire40:58

    Open Source Software for Data Science - J.J. Allaire

    Open-source software is fundamentally necessary to ensure that the tools of data science are broadly accessible, and to provide a reliable and trustworthy foundation for reproducible research.

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  • Object of type ‘closure’ is not subsettable - Jenny Bryan52:49

    Object of type ‘closure’ is not subsettable - Jenny Bryan

    Your first “object of type ‘closure’ is not subsettable” error message is a big milestone for an R user. Congratulations, if there was any lingering doubt, you now know that you are officially...

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  • Welcome to rstudio::conf 20202:32

    Welcome to rstudio::conf 2020

    We opened rstudio::conf with the story of Pim Bongaerts, Data Scientist and Marine Biologist at the California Academy of Sciences.

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  • Not So Standard Deviations Episode 100 - Roger Peng & Hilary Parker59:10

    Not So Standard Deviations Episode 100 - Roger Peng & Hilary Parker

    In episode 100 of Not So Standard Deviations, the first ever episode prepared in advance, Hilary and Roger discuss creativity, its role in data science, & how it can be fostered through conversation.

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  • Panel: Career Advice for Data Scientists - Jen Hecht44:19

    Panel: Career Advice for Data Scientists - Jen Hecht

    This panel will be focused on how you build a career around R! Our panelists are all passionate about R and have each taken a different path to build a career around that passion.

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  • Styling Shiny apps with Sass and Bootstrap 4 - Joe Cheng23:02

    Styling Shiny apps with Sass and Bootstrap 4 - Joe Cheng

    Customizing the style--fonts, colors, margins, spacing--of Shiny apps has always been possible, but never as easy as we’d like it to be.

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  • Total Tidy Tuning Techniques - Max Kuhn23:19

    Total Tidy Tuning Techniques - Max Kuhn

    Many models have structural parameters that cannot be directly estimated from the data. These tuning parameters can have a significant effect on model performance and require some mechanism for...

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  • State of the tidyverse - Hadley Wickham23:22

    State of the tidyverse - Hadley Wickham

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  • Effective Visualizations - Miriah Meyer22:54

    Effective Visualizations - Miriah Meyer

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  • Reproducible Shiny apps with shinymeta - Dr. Carson Sievert21:32

    Reproducible Shiny apps with shinymeta - Dr. Carson Sievert

    Shiny makes it easy to take domain logic from an existing R script and wrap some reactive logic around it to produce an interactive webpage where others can quickly explore different...

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  • Making the Shiny Contest - Mine Çetinkaya-Runde20:50

    Making the Shiny Contest - Mine Çetinkaya-Runde

    In January 2019 RStudio launched the first-ever Shiny contest to recognize outstanding Shiny applications and to share them with the community. We received 136 submissions...

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  • Practical Plumber Patterns - James Blair20:35

    Practical Plumber Patterns - James Blair

    Plumber is a package that allows R users to create APIs out of R functions. This flexible approach allows R processes to be accessed by toolchains and frameworks outside of R.

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  • Stochastic Block Models with R: Statistically rigerous clusting with rigorous code - Nick Strayer24:00

    Stochastic Block Models with R: Statistically rigerous clusting with rigorous code - Nick Strayer

    Often a machine learning research project starts with brainstorming, continues to one-off scripts while an idea forms, and finally, a package is written to disseminate the product.

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  • Data, visualization, and designing AI - Fernanda Viegas & Martin Wattenberg1:00:10

    Data, visualization, and designing AI - Fernanda Viegas & Martin Wattenberg

    Recent progress in machine learning has raised a series of urgent questions: How can we train and debug deep learning models? How can we understand what is going on inside a neural network?

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  • Neural Networks for Longitudinal Data Analysis - Dr. Sydeaka Watson21:59

    Neural Networks for Longitudinal Data Analysis - Dr. Sydeaka Watson

    Longitudinal data (or panel data) arise when observations are recorded on the same individuals at multiple points in time.

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  • 3D ggplots with rayshader - Dr. Tyler Morgan-Wall23:04

    3D ggplots with rayshader - Dr. Tyler Morgan-Wall

    Learn how a single line of code can transform your data visualizations into stunning 3D using the rayshader package.

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  • The Glamour of Graphics - William Chase21:19

    The Glamour of Graphics - William Chase

    I see a lot of ugly charts. This is to be expected as I work with a lot of academics and data scientists, neither of whom have been trained in how to design attractive charts.

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  • MLOps for R with Azure Machine Learning - David Smith20:32

    MLOps for R with Azure Machine Learning - David Smith

    Azure Machine Learning service (Azure ML) is Microsoft’s cloud-based machine learning platform that enables data scientists and their teams to carry out end-to-end machine learning workflows at scale.

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  • R for Graphical Clinical Trial Reporting - Frank Harrell21:58

    R for Graphical Clinical Trial Reporting - Frank Harrell

    Interactive graphical reports go a step further and allow the most important information to be presented by default, while inviting the reviewer to drill down to see other details.

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  • Toward a grammar of psychological experiments - Danielle Navarro22:15

    Toward a grammar of psychological experiments - Danielle Navarro

    Why does a psychological scientist learn a programming language? While motivations are many and varied the two most prominent are data analysis and data collection.

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