Rstudio::conf

rstudio::conf 2019 Workshop materials now available

Mine Çetinkaya-Rundel

Braulio Cuandon & Ana Alyeska Santos | Using R to Create Reproducible Engineering Test Reports

Talk from rstudio::conf(2020) Engineers at Biosense Webster, a Johnson and Johnson medical device company that specializes in diagnosing and treating cardiac arrhythmias, write multiple test reports to comply with FDA regulatory standards. These intricate reports require 36 hours of an engineer’s time on average, constraining the engineers from completing investigations and studies in a timely matter. Writing scripts in R that create reproducible reports can significantly reduce the time spent by an engineer creating these reports allowing them to do a much thorough investigation with a larger scope. Through Shiny, engineers could conveniently have their parameters and recorded data processed and stored in a database by accessing a web link and filling out the required information within a user-friendly interface. Upon the generation of the report, accurate and properly formatted test reports, compliant to both the company and FDA regulatory standards, are produced through Rmarkdown and knitr knitting all the outputs with complete data analysis tools such as normality plots and process capability measurements to a word document that follows company required headers, footers, and headings. The reproducible report creation shown in this report can be extended to other types of test reports and protocols. The pilot phase that has been conducted has shown that complete report production has been decreased from 36 hours to an hour

Paige Bailey | Deep Learning with R | RStudio (2020)

Originally posted to https://rstudio.com/resources/rstudioconf-2020/deep-learning-with-r/ Paige Bailey is the product manager for TensorFlow core as well as Swift for TensorFlow. Prior to her role as a PM in Google's Research and Machine Intelligence org, Paige was developer advocate for TensorFlow core; a senior software engineer and machine learning engineer in the office of the Microsoft Azure CTO; and a data scientist at Chevron. Her academic research was focused on lunar ultraviolet, at the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, CO, as well as Southwest Research Institute (SwRI) in San Antonio, TX

Tidyverse Train-the-Trainer Certification Workshop - rstudio::conf(2019L)

What is the 2-day Tidyverse Train-the-Trainer Workshop? That's a great question, I'm glad you asked. Register at https://rstd.io/conf Learn more at https://rstd.io/conf-agenda ------------------------ Tidyverse Train-the-Trainer Certification Workshop - 2 Days - Day 1 of the course will be co-taught by Mine Cetinkaya-Rundel and Garrett Grolemund, RStudio Data Scientists and Professional Educators. - On Day 2, Mine will teach the Shiny track and Garrett will teach the Tidyverse track. This two-day workshop will equip you to teach R effectively. We will draw on RStudio's experience teaching R to recommend tips for designing, teaching, and supporting short R courses. On Day 1 of the course, you will learn practical activities that you can use immediately to improve your presentation style, learning outcomes, and student engagement. You will leave the class with a cognitive model of learning that you can use to develop your own effective workshops or courses within your organization. The course will also cover how to use RStudio Cloud and its curriculum of tutorials to jump-start your own lessons. On Day 2 of the course, participants will have the option to choose one of two tracks: Teaching the Tidyverse or Teaching Shiny. - Teaching the Tidyverse: Classroom examples will focus on how to teach students to do data analysis with the Tidyverse. We will use Master the Tidyverse, which is an award-winning two-day workshop developed by RStudio, as an example. Participants will receive the course materials for teaching Master the Tidyverse. You should take this workshop if you work for a training partner and want to qualify as an RStudio Certified Tidyverse Instructor or if you are an advocate for R in your organization. You should be proficient in the Tidyverse already and be prepared to submit examples of your work. Prior teaching experience is helpful, but not required. Please bring a laptop and a device that has video recording capabilities (such as a laptop or cell phone). Instructors: Garrett Grolemund, Mine Çetinkaya-Rundel

Mine Çetinkaya-Rundel

Machine Learning with R and TensorFlow

J.J. Allaire's keynote at rstudio::conf 2018 on the R interface to TensorFlow (https://tensorflow.rstudio.com), a suite of packages that provide high-level interfaces to deep learning models (Keras) and standard regression and classification models (Estimators), as well as tools for cloud training, experiment management, and production deployment. The talk also discusses deep learning more broadly (what it is, how it works, and where it might be relevant to users of R in the years ahead). Slides: https://beta.rstudioconnect.com/ml-with-tensorflow-and-r/ JJ Allaire: - https://github.com/jjallaire Twitter: @fly_upside_down https://twitter.com/fly_upside_down Related blog post: https://blog.rstudio.com/2018/02/06/tensorflow-for-r/

JJ Allaire