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  1. NFL machine learning capstone

project workflow

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Last updated 1 year ago

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The jobs are meant to run autonomously, but for demo purposes we can manually run the ETL and feature selection jobs from the notebooks/nfl_load_nflverse_data_demo.ipynb notebook.

  • nfl_load_nflverse_data_demo.ipynb - demos manually running the load and build jobs (nfl_00 - 01)

  • nfl_perform_feature_selection_demo.ipynb - demos manually running weekly stats and feature selection jobs (nfl_02 - 04)

Job
Stage
Description

nfl_main.py

orchestration

runs the ETL and feature selection for the win/loss model

nfl_00_load_nflverse_data.py

ETL

downloads the nflverse data into local storage

nfl_01_build_nfl_database.py

ETL

builds the nfl database from the nflverse data

nfl_02_prepare_weekly_stats.py

Experiment 2

merges metrics from all datasets into a single stats dataset

nfl_03_perform_feature_selection.py

Experiment 2

performs feature selection on the nfl data

nfl_04_merge_game_features.py

Experiment 2

merge our features with the core nfl play actions dataset

Finally, we can run the

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Experiment 2 notebook
NFL Workflow