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created heroku app, added read me #5

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69fc2af
uploading team model
oferbaharav Mar 5, 2020
d87e554
add Procfile and runtime.txt
oferbaharav Mar 5, 2020
538bad9
adding readme and original model as airbnb_notebook
oferbaharav Mar 6, 2020
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22 changes: 22 additions & 0 deletions Pipfile
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[[source]]
name = "pypi"
url = "https://pypi.org/simple"
verify_ssl = true

[dev-packages]

[packages]
flask = "*"
flask-sqlalchemy = "*"
flask-migrate = "*"
requests = "*"
python-dotenv = "*"
pandas = "*"
numpy = "*"
sklearn = "*"
gunicorn = "*"
psycopg2-binary = "*"
joblib = "*"

[requires]
python_version = "3.7"
363 changes: 363 additions & 0 deletions Pipfile.lock
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1 change: 1 addition & 0 deletions Procfile
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web: gunicorn app:app
9 changes: 8 additions & 1 deletion README.md
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# Data-Science
# Data-Science

For this project, our goal is to accurately predict the price of a potential listing for AirBnB in the city of Berlin, Germany.

## Notebook

The notebook for this repo 'airbnb_notebook.ipynb' is used to take 'Berlin.csv' which
is taken and cleaned up from the original at https://www.kaggle.com/brittabettendorf/berlin-airbnb-data and turn that into a predictive model for prices of airbnb listings in the Berlin area. This model is persisted to `berlin_model.gz` as a compressed joblib dump (instead of pickle). Next `app.py` reads this model and uses it to make predictions in the web interface, for now arranged as html under `templates/`. `features.json`contains a skeleton JSON of feature variables with default values set to '0', and is used to transform html form input into a format used to do the model prediction. `requirements.txt`, `runtime.txt`, and `Procfile` are all necessary to run on Heroku.
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