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*.pkl filter=lfs diff=lfs merge=lfs -text
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*.xgb filter=lfs diff=lfs merge=lfs -text
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README.md
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# Air Quality Forecast
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<a target="_blank" href="https://cookiecutter-data-science.drivendata.org/">
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<img src="https://img.shields.io/badge/CCDS-Project%20template-328F97?logo=cookiecutter" />
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</a>
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A short description of the project.
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## Project Organization
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```
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βββ LICENSE <- Open-source license if one is chosen
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βββ Makefile <- Makefile with convenience commands like `make data` or `make train`
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βββ README.md <- The top-level README for developers using this project.
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βββ data
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β βββ external <- Data from third party sources.
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β βββ interim <- Intermediate data that has been transformed.
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β βββ processed <- The final, canonical data sets for modeling.
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β βββ raw <- The original, immutable data dump.
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β
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βββ docs <- A default mkdocs project; see www.mkdocs.org for details
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β
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βββ models <- Trained and serialized models, model predictions, or model summaries
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β
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βββ notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
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β the creator's initials, and a short `-` delimited description, e.g.
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β `1.0-jqp-initial-data-exploration`.
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β
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βββ pyproject.toml <- Project configuration file with package metadata for
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β air-quality-forecast and configuration for tools like black
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β
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βββ references <- Data dictionaries, manuals, and all other explanatory materials.
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β
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βββ reports <- Generated analysis as HTML, PDF, LaTeX, etc.
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β βββ figures <- Generated graphics and figures to be used in reporting
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β
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βββ requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
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β generated with `pip freeze > requirements.txt`
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β
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βββ setup.cfg <- Configuration file for flake8
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β
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βββ air-quality-forecast <- Source code for use in this project.
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β
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βββ __init__.py <- Makes air-quality-forecast a Python module
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β
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βββ config.py <- Store useful variables and configuration
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β
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βββ dataset.py <- Scripts to download or generate data
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β
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βββ features.py <- Code to create features for modeling
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β
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βββ modeling
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β βββ __init__.py
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β βββ predict.py <- Code to run model inference with trained models
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β βββ train.py <- Code to train models
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β
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βββ plots.py <- Code to create visualizations
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```
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--------
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# air-quality-forecast
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