rstudio::conf 2019

  • RStudio Connect Past, present, and future - Jeff Allen22:16

    RStudio Connect Past, present, and future - Jeff Allen

    RStudio Connect is a publishing platform that helps to operationalize the data science work you're doing. We'll review the current state and unveil some exciting new features.

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  • Shiny in production: Principles, practices, and tools - Joe Cheng50:26

    Shiny in production: Principles, practices, and tools - Joe Cheng

    Shiny is a web framework for R. As such, Shiny has always faced questions about whether it can or should be used “in production" we will answer these questions in this talk.

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  • Welcome and RStudio Vision - Tareef Kawaf28:32

    Welcome and RStudio Vision - Tareef Kawaf

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  • Working with names and expressions in your tidy eval code - Lionel Henry16:10

    Working with names and expressions in your tidy eval code - Lionel Henry

    In practice there are two main flavors of tidy eval functions: functions that select columns, such as `dplyr::select()`, and functions that operate on columns, such as `dplyr::mutate()`.

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  • Why TensorFlow eager execution matters - Sigrid Keydana21:06

    Why TensorFlow eager execution matters - Sigrid Keydana

    In current deep learning with Keras and TensorFlow, when you've mastered the basics and are ready to dive into more involved applications (such as generative networks, sequence-to-sequence or...

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  • Visualizing uncertainty with hypothetical outcomes plots - Claus Wilke21:29

    Visualizing uncertainty with hypothetical outcomes plots - Claus Wilke

    Uncertainty is a key component of statistical inference. However, uncertainty is not easy to convey effectively in data visualizations. For example, viewers have a tendency to...

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  • vctrs: Tools for making size and type consistent functions - Hadley Wickham22:16

    vctrs: Tools for making size and type consistent functions - Hadley Wickham

    vctrs is a new package that provides tools (cognitive and computational) to ensure that functions behave consistently with respect to inputs of varying length and type. The end goal of vctrs is...

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  • Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition - Matt Dancho20:19

    Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition - Matt Dancho

    An organization that loses 200 high-performing employees per year has a lost productivity cost of about $15M/year. This cost is massive, yet many organizations don’t know it exists.

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  • pagedown: Creating beautiful PDFs with R Markdown and CSS - Yihui Xie20:58

    pagedown: Creating beautiful PDFs with R Markdown and CSS - Yihui Xie

    The traditional way to beautiful PDFs is often through LaTeX or Word, but have you ever thought of printing a web page to PDF? Web technologies (HTML/CSS/JavaScript) are becoming more and more...

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  • Explicit Direct Instruction in Programming Education - Felienne56:09

    Explicit Direct Instruction in Programming Education - Felienne

    In education, there is and has always been debate about how to teach. One of these debates centers around the role of the teacher: should their role be minimal, allowing students to find and...

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  • Melt the clock Tidy time series analysis - Earo Wang20:02

    Melt the clock Tidy time series analysis - Earo Wang

    Time series can be frustrating to work with, particularly when processing raw data into model-ready data. This work presents two new packages that address a gap in existing methodology for...

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  • The unreasonable effectiveness of public work - David Robinson40:40

    The unreasonable effectiveness of public work - David Robinson

    In this talk, I'll lay out the reasons that blogging, open source contribution, and other forms of public work are a critical part of a data science career.

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  • The resilient R champion - Tonya Filz17:32

    The resilient R champion - Tonya Filz

    Merriam-Webster defines resilience as the ability to recover from or adjust easily to misfortune or change. As a Customer Success Representative who works alongside data scientists using RStudio’s...

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  • The next million R users - Carl Howe20:27

    The next million R users - Carl Howe

    Many students believe that R is obscure, complex, and difficult to write. However, data from a new large-scale survey of R users conducted by RStudio shows that new R users are taking...

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  • The lazy and easily distracted report writer: Using rmarkdown and parameterised reports - Mike K Smith15:33

    The lazy and easily distracted report writer: Using rmarkdown and parameterised reports - Mike K Smith

    My brain is lazy, shallow and easily distracted. Learn how I use notebooks to keep my present-self organised, my future-self up to speed with what I was thinking months ago, and also how I use...

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  • The Future's Shiny: Dashboards for Pioneering Genomic Medicine in R - Nic Crane19:06

    The Future's Shiny: Dashboards for Pioneering Genomic Medicine in R - Nic Crane

    Shiny’s expanding capabilities are rapidly transforming how it is used in an enterprise. This talk details the creation of a large-scale application, supporting hundreds of concurrent users, making...

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  • Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops - Tracy Teal19:51

    Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops - Tracy Teal

    The Carpentries is an open, global community teaching researchers the skills to turn data into knowledge. Since 2012 we have taught 700+ R workshops & trained 1600+ volunteer instructors.

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  • Teaching data science with puzzles - Irene Steves21:50

    Teaching data science with puzzles - Irene Steves

    Of the many coding puzzles on the web, few focus on the programming skills needed for handling untidy data. During my summer internship at RStudio, I worked with Jenny Bryan to develop...

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  • Spatial data science in the Tidyverse - Edzer Pebesma19:49

    Spatial data science in the Tidyverse - Edzer Pebesma

    Package sf (simple feature) and ggplot2::geom_sf have caused a fast uptake of tidy spatial data analysis by data scientists. Important spatial data science challenges are not handled by...

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  • Solving the model representation problem with broom - Alex Hayes20:30

    Solving the model representation problem with broom - Alex Hayes

    The R objects used to represent model fits are notoriously inconsistent, making data analysis inconvenient and frustrating. The broom package resolves this issue by defining a consistent way to...

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