Jimmykarterba / Machine-Learning-Deployment-Tutorials

Sample end to end projects from data collection to putting models into production

Machine Learning Deployment Tutorials

Sample end to end projects from data collection to putting models into production.

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1. Predict Sales

Check out the corresponding medium blog post https://towardsdatascience.com/how-to-easily-deploy-machine-learning-models-using-flask-b95af8fe34d4.

Environment and tools

1. scikit-learn
2. pandas
3. numpy
4. flask

Installation

pip install scikit-learn pandas numpy flask

python model.py

python app.py

2. Predict House Prices

Download the dataset from here.

Environment and tools

1. scikit-learn
2. pandas
3. numpy
4. flask
5. docker

Installation

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}

Output:

{
  "predict cost": 1022545.34768284
}

Citing

@misc{Abhinav:2019,
  Author = {Abhinav Sagar},
  Title = {Machine-Learning-Deployment-Tutorials},
  Year = {2019},
  Publisher = {GitHub},
  Journal = {GitHub repository},
  Howpublished = {\url{https://github.com/abhinavsagar/Machine-Learning-Deployment-Tutorials}}
}