talk-data.com

External registration required at nyhackr.

This month we have Max Kuhn giving a talk about tidymodels.

After the talk we will give away both an in-person and a virtual ticket to The Data Science and AI Conference (the spiritual successor of the NY R Conference) taking place August 25-27. Members of this meetup can get a 20% discount on tickets with code nyhackr.

Thank you to NYU for hosting us.

Everybody attending must RSVP through the registration form at nyhackr. There is a charge for in-person and virtual tickets are free.

Space is extremely limited and in-person registration closes at 3 PM the day of the talk.

About the Talk: A lot! I’ll discuss updates to tidymodels related to: postprocessing, sparse data, multiparameter optimization, parallel processing, mirai, catboost, quantile regression, ordinal data, AI, and two new packages.

About Max: Max Kuhn is a Scientist at Posit, PBC (nee RStudio). He is working on improving R’s modeling capabilities and maintaining about 30 packages, including caret. He was a Senior Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He has been applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics. 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. He has co-written several other books: Feature Engineering and Selection, Tidy Models with R, and Applied Machine Learning for Tabular Data (in process).

The venue doors open at 6:30 PM America/New_York where we will continue enjoying pizza together (we encourage the virtual audience to have pizza as well). The talk, and livestream, begins at 7:00 PM America/New_York.

Remember, register at nyhackr.

Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end Understand how to use different modeling and feature engineering approaches fluently Examine the options for avoiding common pitfalls of modeling, such as overfitting Learn practical methods to prepare your data for modeling Tune models for optimal performance Use good statistical practices to compare, evaluate, and choose among models