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custonova's Introduction

Custonova

Intro

  • This project consist of two type of applications a django application and an angular application.
  • This implies that the backend project and the frontend must be running for you to be able to use your system.

This repository contains the code for a customer churn project using KMeans clustering and logosticregreasion to predict the probability of a customer to stay loyal to the shop or not .

The project uses the following technologies:

  • Python - The programming language used to develop the project.
  • Sklearn - A machine learning library used to train the AI model.
  • Django - A web framework used to create the REST API.
  • Angular - A web framework used to create the frontend UI.

The project is divided into the following three parts:

  • Model training - This part of the project uses Sklearn and TensorFlow to train the AI model. The model is trained on a dataset of fraudulent and non-fraudulent transactions.
  • REST API - This part of the project uses Django to create a REST API that exposes the AI model. The REST API can be used to get predictions from the AI model.
  • Frontend UI - This part of the project uses Angular to create a frontend UI that consumes the REST API. The frontend UI allows users to input transaction data and get predictions from the AI model.

Backend

  • Activate anaconda environment
  • Run the following commands sequentially.

cd custonova && pip install -r requirements.txt && python manage.py makemigrations && python manage.py migrate && python manage.py createsuperuser && python manage.py runserver

Frontend

  • run the following commands sequentially.

bash npm i -g @angular/cli or yarn global add @angular/cli cd front npm install or yarn ng serve -o --hmr

  • enjoy

custonova's People

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