Machine learning Web Server

Boilerplate template to build end-end to machine learning model using scikit-learn and deploy the model as REST api using Flask

This boilerplate template provides two end points, one is create_model which takes the dataset file and the target field then build training pipeline and persist the model. The second endpoint is predict for model inference, which takes single record and produces the model prediction.

Usage

Run server locally

Clone the repository

git clone https://github.com/kantharajucn/ML_web_server_boilerplate
change directory into the repo

cd path/to/ML_web_server
Install requirements

pip install -r requirements.txt
Run Flask application

make run
Run tests

make test

Run server using Docker

Build docker image

make docker-build
Run docker image

make docker-run
Run tests

make docker-test
Stop docker container

make docker-down

Web server is available on the port 8000.