pratos / flask_api

Creating a Machine Learning API using Flask - Repository for AV Article

Home Page:https://www.analyticsvidhya.com/blog/2017/09/machine-learning-models-as-apis-using-flask/

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Code accompanying the AnalyticsVidhya article

NOTE: This code is a bit old, please do not use this for production level tasks. There are better ways to do all these things, consider using FlaskAppBuilder & quart or FastAPI for your production apis

How to setup the Anaconda environment:

  • Make sure you have Anaconda distribution, if not then visit: Miniconda Installation to install it.
  • For a faster installation, run command (on terminal): curl -L mini.conda.ml | bash (Courtesy: @mikb0b)
  • For any queries regarding conda environment, visit: Managing Conda Environments
  • Go to the folder ./flask_api, you'll encounter flask_api.yml file.
  • In the terminal run command: conda env create -f flask_api.yml
  • Once done, run: source activate flask_api. Your virtual environment is setup successfully!

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Creating a Machine Learning API using Flask - Repository for AV Article

https://www.analyticsvidhya.com/blog/2017/09/machine-learning-models-as-apis-using-flask/

License:MIT License


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