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:
- data management
- data explore
- model train
- 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
pipenv install
# Serve API on localhost:8000
pipenv run python manage.py runserver
snapshot
login page
model train page
prediction page
