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Join R-Ladies DC and R-Ladies Philly in June for an evening of short and insightful talks related to using R. Topics will highlight the breadth of use cases our members solve using R and the packages they love.

We will update the zoom link before the event.

Agenda:
6:00 - 6:10 - Join online
6:10 - 6:15 - Welcome and announcements
6:15 - 7:30 - Talks

Speakers and Talk Abstracts (in order of presentation):

  • ‘Data wrangling in R for SAS users‘ by Priyanka Gagneja
    This talk is about how to make it easy to translate legacy SAS codes with R. This can be a good starting point for SAS programmers who don't know much R and for R users who do not know SAS.
  • ‘Leveraging Open-Source Communities for Professional Development’ by Hebah Bukhari
    A few years ago I made a career switch and picked up R as a coding language. I didn’t have any coding background before. I began in an accredited program, but everything I learned about R and coding has been through the contribution of the R community and the help of its generous members.
  • ‘Imaging R: An Interactive Web Application for Visualizing Multimodality Imaging Data Using R and Shiny’ by Kiki Zhang
    I developed an R-based web application that provides interactive image processing, analysis, and visualization. Multimodal data can be explored intuitively through the analysis pipelines comprising spectral density and time-lagged cross-correlation analyses for quantifying variation in neuronal dynamics and observing interaction dynamics patterns between signals.
  • ‘Using the OpenAI API With Your Prompt + Your Data’ by Abigail Haddad
    I'll show how I'm using the R openAI package to work with the GPT-4 API. My example involves creating fake resumes by combining custom prompts with job-related data from a .csv file, showing how we can use the API to iterate through a dataset for text generation. I'll also mention a couple of NLP projects that I'm doing that use the same general format of prompt + iterating through text.
  • ‘Tidyverse Style Guide’ by Arati Krishnamoorthy
    A guide to using the tidyverse style guide.
Data Analytics
Data Science
Predictive Analytics
R Project for Statistical Computing
Programming in R

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