Founded by Josh Reich and Drew Conway, the New York Open Statistical Programming Meetup started as the New York R Meetup with a handful of people in an office at Union Square Ventures. Since then it has grown to over 11,000 members and has been hosted at NYU, Columbia, AOL, iHeartRadio, eBay, Work-Bench and other locations.
Our mission is to spread knowledge of statistical programming techniques in open-source languages such as R, Python, Julia and Go, and data science in general. Another important aspect is community building and socializing. The meetups start with pizza, followed by a 45-90 minute talk, ending with a trip to the local bar.
To attend please visit the meetup page.
Whenever possible we make presentations available at the Presentations page.
Job openings and other announcements are on the meetup discussion board.
Max Kuhn returns again to tell us about new happenings in tidymodels.
This meetup is the runup to the 2021 Government & Public Sector R Conference and Workshops taking place virtually December 8-10. Members of the group can use code nyhackr for a 20% discount at https://rstats.ai/gov/.
Thank you to EcoHealth Alliance for providing the Zoom link.
Conversations during the meetup are encouraged in the monthly-meetup-chat channel in the nyhackr slack: https://nyhackr.org/slack.html
About the Talk:
The tidymodels framework is a collection of packages for modeling and machine learning using tidyverse principles. We've been working hard to add new features and fix bugs. I'll talk about censored regression, model deployment, case weights, and other features in progress. Additionally, the results from this year's user poll will be shown.
Max Kuhn is a software engineer at RStudio. He is currently working on improving R's modeling capabilities. He was a Senior Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics. Max is the author of numerous R packages for techniques in machine learning and reproducible research. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015. Their second book, Feature Engineering and Selection, was published in 2019.
The talk will begin at 7 PM America/New_York and we will start admitting people to the event shortly before. Since this is completely remote there will be no pizza but everyone is encouraged to have pizza individually.
If you wish to contribute to the website the process is pretty simple.