Launch machine learning models into production using flask, docker etc.
Check out the corresponding medium blog post https://towardsdatascience.com/how-to-easily-deploy-machine-learning-models-using-flask-b95af8fe34d4.
- scikit-learn
- pandas
- numpy
- flask
pip install scikit-learn pandas numpy flask
python model.py
python app.py
Download the dataset from here.
- scikit-learn
- pandas
- numpy
- flask
- docker
docker-compose up --build
curl -X POST -H "Content-Type: application/json" -d @to_predict_json.json http://localhost:8080/predict_price
where to_predict.json
contains:
{"grade":9.0,"lat":37.45,"long":12.09,"sqft_living":1470.08,"waterfront":0.0,"yr_built":2008.0}
or
curl -X POST -H "Content-Type: application/json" -d '{"grade":9.0,"lat":37.45,"long":12.09,"sqft_living":1470.08,"waterfront":0.0,"yr_built":2008.0}' http://localhost:8080/predict_price
Output:
{
"predict cost": 1022545.34768284
}
If you find this code useful in your research, please consider citing the blog:
@misc{sagardeploy,
Author = {Abhinav Sagar},
Title = {How to Easily Deploy Machine Learning Models Using Flask},
Year = {2019},
Journal = {Towards Data Science},
}
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