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appflask's Introduction

Machine Learning Deployment Tutorials

Launch machine learning models into production using flask, docker etc.

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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

Logo

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}}
}

Contacts

If you want to keep updated with my latest articles and projects follow me on Medium. These are some of my contacts details:

  1. Personal Website
  2. Linkedin
  3. Medium
  4. GitHub
  5. Kaggle

appflask's People

Contributors

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Watchers

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