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bookclub-tmwr's Introduction

R4DS Tidy Modeling with R Book Club

Welcome to the R4DS Tidy Modeling with R Book Club!

We are working together to read Tidy Modeling with R by Max Kuhn and Julia Silge. Join the #book_club-tidy_modeling_with_r channel on the R4DS Slack to participate. As we read, we are producing notes about the book.

Meeting Schedule

If you would like to present, please add your name next to a chapter using the GitHub Web Editor!

Cohort 1: (starts 2021-01-05) - Tuesdays, 8:00pm EST/EDT

  • 2021-01-05: Chapter 1: Software for modeling: Jon Harmon
  • 2021-01-12: Chapter 2: A tidyverse primer: Jonathan Trattner
  • 2021-01-19: Chapter 3: A review of R modeling fundamentals: Tony ElHabr
  • 2021-01-26: Chapter 4: The Ames housing data: Tan Ho
  • 2021-02-02: Chapter 5: Spending our data: Asmae Toumi
  • 2021-02-09: Chapter 6: Feature engineering with recipes: Pavitra Chakravarty
  • 2021-02-16: Chapter 7: Fitting models with parsnip: Jordan Krogmann
  • 2021-02-23: Chapter 8: A model workflow: Ben Gramza
  • 2021-03-02: Chapter 9: Judging model effectiveness: Joe Sydlowski
  • 2021-03-09: Q&A with authors Max Kuhn & Julia Silge: Chapters 1-9
  • 2021-03-16: Chapter 10: Resampling for evaluating performance: Asmae Toumi
  • 2021-03-23: Chapter 11: Comparing models with resampling: Jon Harmon
  • 2021-03-30: Chapter 12: Modeling tuning and the dangers of overfitting
  • 2021-04-06: Chapter 13: Grid search
  • 2021-04-13: Chapter 14: Iterative search
  • 2021-04-20: Review: Chapters 10-14

Cohort 3: - Mondays, 11:00am CDT - facilitated by Ildiko Czeller

  • 2021-03-29: Chapter 1: Software for modeling: Ildiko Czeller
  • 2021-04-05: Chapter 2: A tidyverse primer: TBD
  • 2021-04-12: Chapter 3: A review of R modeling fundamentals: TBD
  • 2021-04-19: Chapter 4: The Ames housing data: TBD
Future Meetings
  • 2021-04-26: Chapter 5: Spending our data
  • 2021-05-03: Chapter 6: Feature engineering with recipes
  • 2021-0?-??: Chapter 7: Fitting models with parsnip
  • 2021-0?-??: Chapter 8: A model workflow
  • 2021-0?-??: Chapter 9: Judging model effectiveness
  • 2021-0?-??: Chapter 10: Resampling for evaluating performance
  • 2021-0?-??: Chapter 11: Comparing models with resampling
  • 2021-0?-??: Chapter 12: Modeling tuning and the dangers of overfitting
  • 2021-0?-??: Chapter 13: Grid search
  • 2021-0?-??: Chapter 14: Iterative search

How to Present

This repository is structured as a {bookdown} site. To present, follow these instructions:

  1. Setup Github Locally
  2. Fork this repository.
  3. Create a New Project in RStudio using your fork.
  4. Install dependencies for this book with devtools::install_dev_deps() (technically optional but it's nice to be able to rebuild the full book).
  5. Create a New Branch in your fork for your work.
  6. Edit the appropriate chapter file. Use ## to indicate new slides (new sections).
  7. If you use any packages that are not already in the DESCRIPTION, add them. You can use usethis::use_package("myCoolPackage") to add them quickly!
  8. Commit your changes.
  9. Push your changes to your branch.
  10. Open a Pull Request (PR) to let us know that your slides are ready.

When your PR is checked into the main branch, the bookdown site will rebuild, adding your slides to this site.

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Contributors

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