SmartCampus AI - Risk Analytics Service

This repository contains the source code for the Risk Analytics microservice of the SmartCampus AI project. It is a lightweight Python service that uses a machine learning model to predict the likelihood of a student becoming disengaged or failing.

✨ Features

° Predictive REST API: A simple and efficient Flask endpoint that receives student data and returns a predictive risk score.

° Machine Learning Model: Utilizes a pre-trained Logistic Regression model from Scikit-learn to analyze factors like attendance, marks, and fee status.

° Decoupled Microservice: Designed to run independently of the core backend, allowing for separate scaling, updates, and maintenance of the AI engine.

🛠️ Tech Stack

° Framework: Flask

° Language: Python

° ML Library: Scikit-learn, Pandas

° Containerization: Docker

🚀 Getting Started

Prerequisites

Python (v3.9 or later)

pip

Installation

1. Clone the repository: git clone https://github.com/viru0909-dev/ERP_ML.git
2. Install dependencies: pip install -r requirements.txt
3. Run the Flask application: flask run The service will be available at http://127.0.0.1:5000.

🔌 API Usage

Send a POST request to the /predict endpoint with a JSON payload containing student data.

Endpoint: /predict Method: POST

Example Request Body:

JSON

{ "attendance": 75.5, "marks": 62.0, "fees_paid": true } Example Success Response:

JSON

{ "risk_probability": 0.68 }