Machine Learning System

introduction

This project is a full stack Django/React/Redux app that uses token based authentication with Knox.

Then I add Machine Learning features for demostrate the full workflow of the data mining, including the four stage corresponding to four pages:

1. data management
2. data explore
3. model train
4. prediction

The data set is the classic iris data, which is only for demo, and this project is from my interest. so you can reference, but the quality is not assured.

features

• authentication functions

login from login page register your account logout from inner page

• data management

input iris items edit iris items delete iris items

• data explore

inspect attribute distribution through histogram inspect sepal distribution through scatter graph inspect petal distribution through scatter graph

• model train

input cluster number train a cluster model using sklearn-kmeans library inspect cluster result through sepal and petal scatter

• prediction

input iris sepal and petal attributes predict iris cluster

technology stack

category	name	comment
frontend	reactjs	frontend framework
frontend	redux	state management
frontend	react-C3JS	D3 based graph tool
frontend	react-bootstrap	style component library
frontend	data-ui	react data visualization tool
backend	django	backend framework
backend	django-rest-knox	authentication library
backend	djangorestframework	restful framework
backend	sklearn	machine learning tool

Quick Start

# Install dependencies
cd ./frontend
npm install

# Build for production
npm run build


# Install dependencies
cd ../backend
pip3 install pipenv
pipenv install

# Serve API on localhost:8000
pipenv run python manage.py runserver

deploy on production environment

run on wsgi server(uwsgi)

pipenv run uwsgi --http :9090 --wsgi-file config/wsgi.py --check-static ../frontend/dist/

run on nginx + uwsgi

there are two points needed to modified: (1) the root path of default file root /root/win10/mine/machine_learning_system/frontend/dist/; (2) the user role of nginx.conf file user root;

apt update
apt install nginx

pipenv run uwsgi --socket :9090 --wsgi-file config/wsgi.py

cp -f ./config/default /etc/nginx/sites-available/default
cp -f ./config/nginx.conf /etc/nginx/nginx.conf
nginx&

snapshot

login page

model train page

prediction page