https://github.com/soulyma/devices-price-classification-system-using-python-and-django
Devices Price Classification System (AI System) using Python and linked with Django
https://github.com/soulyma/devices-price-classification-system-using-python-and-django
ai artificial-intelligence django-project django-rest-framework machine-learning matplotlib ml numpy pandas python seaborn sklearn
Last synced: 6 months ago
JSON representation
Devices Price Classification System (AI System) using Python and linked with Django
- Host: GitHub
- URL: https://github.com/soulyma/devices-price-classification-system-using-python-and-django
- Owner: Soulyma
- Created: 2024-04-21T17:18:11.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-21T17:29:23.000Z (over 1 year ago)
- Last Synced: 2025-02-13T09:32:14.073Z (8 months ago)
- Topics: ai, artificial-intelligence, django-project, django-rest-framework, machine-learning, matplotlib, ml, numpy, pandas, python, seaborn, sklearn
- Language: Jupyter Notebook
- Homepage:
- Size: 4.43 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Devices-Price-Classification-System-using-Python-and-Django
Devices Price Classification System (AI System) using Python and linked with Django
Mainly the system include two small projects:
* Python project: will allow you to predict the prices, allowing the sellers to classify the device's prices according to their characteristics
* Django project: Will contain a simple entity, and a few endpoints, to call the service from the Python project for a bunch of test cases, and store them.
EndPoints:
* POST /api/devices/: Retrieve a list of all devices
* GET /api/devices/{id}: Retrieve details of a specific device by ID.
* POST /api/devices: Add a new device.
* POST /api/predict/{deviceId}
# How to run :
Go to django side and type the following command
``` CMD
python manage.py runserver
```
Then four endpoints can be accessed :
1. Adding a new device
2. Getting a list of all the devices
3. Getting a device from id
4. Predict the device price range based on the id
For more details check postman `Device Price.postman_collection.json` file