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An application to detect fraud automobile insurance claims using Logistic regression ML model. Presents a simple UI developed using ReactJS which is integrated with the ML model backend using Flask API.

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chris287/reactFlaskMl

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reactFlaskMl

This is an ML application developped using ReactJs and Python. It uses Logistic regression model to predict wheather the automobile insurance claims are fraudlent or not. Flask API is used to get the request from the client side and send back the predicted response.

Getting Started

Clone the repository by entering git clone https://github.com/chris287/reactFlaskMl.git

The scripts directory contains all the python scripts and ui directory consists of the ReactJs code for frontend UI.

Navigate inside scripts directory and run command pip install -r requirements.txt in cmd to install all the required libraries for python.In the same way navigate inside ui and run npm i to install node modules.

To start the flask API server,navigate scripts] directory and run python main.py.This will start a development server on http://127.0.0.1:5000/ for python flask API.Run the server by opening the link in browser.Next step is to load the ui.To do this run the command npm start inside ui directory. This will start a react server and you can access the ui.

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An application to detect fraud automobile insurance claims using Logistic regression ML model. Presents a simple UI developed using ReactJS which is integrated with the ML model backend using Flask API.

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