https://github.com/jthomasmock/nfl_hanic

Slides for my HANIC presentation
https://github.com/jthomasmock/nfl_hanic

Last synced: 22 days ago
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Slides for my HANIC presentation

• Host: GitHub
• URL: https://github.com/jthomasmock/nfl_hanic
• Owner: jthomasmock
• Created: 2020-05-21T00:19:18.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-05-22T14:22:58.000Z (over 4 years ago)
• Last Synced: 2024-12-18T01:08:45.953Z (23 days ago)
• Language: HTML
• Homepage: https://jthomasmock.github.io/nfl_hanic
• Size: 630 KB
• Stars: 7
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# NFL HANIC 

Slides for my HANIC presentation

You can find the longer form writeup on my blog at [themockup.blog](https://themockup.blog/) -- this will be a true statement... in the future. For now the slide deck is my writeup!

To get the 2.2 GB of raw data you'll need to download the data from 2000-2019 via `nflfastR`, otherwise my code as included should get you to the end result.

Full Disclosure:

- The Random Forest model takes about 20 min to run w/ 1000 trees.

- You lose about 3% accuracy w/ only 100 trees but cut your run time down to 2 min

- The logistic regression is almost as accurate as the Random Forest model and takes about 2 min as well

![Thank you `nflscrapR` and `nflfastR`](thank_you.png)

# Learn more about `tidymodels`

* [`tidymodels`.org](https://www.tidymodels.org/learn/) has step by step guides of various complexities

* I'll be adding additional NFL-focused examples at: [TheMockup.blog](https://themockup.blog/posts/2020-05-01-tidy-long-models/)

* Julia Silge's (a `tidymodels` maintainer) [blog](https://juliasilge.com/) or [video series](https://www.youtube.com/channel/UCTTBgWyJl2HrrhQOOc710kA)  

  * She has 10+ videos/blogposts covering various aspects of the full pipeline

  * Most recently covered [predicting Beach Volleyball winners](https://juliasilge.com/blog/xgboost-tune-volleyball/) w/ a tuned XGBoost model

* Alison Hill's [Workshop from rstudio::conf2020](https://conf20-intro-ml.netlify.app/)

* Gentle Intro to `tidymodels` on [RStudio RViews blog](https://rviews.rstudio.com/2019/06/19/a-gentle-intro-to-tidymodels/)

* Julia Silge's online [free interactive course](https://supervised-ml-course.netlify.app/)