Money Laundering Prevention System

🔗 Deployed Website on Streamlit Cloud Link

This project aims to predict the likelihood of backorders for products in a supply chain using machine learning techniques.
Backorders occurs when a product is temporarily out of stock, and customers need to wait for it to become available again. By predicting potential backorders of a product, businesses can proactively manage their inventory and improve customer satisfaction.

Screenshots of UI

Project demo video

project-demo-video.mp4

Usage

1. Install required packages.

pip install -r requirements.txt

2. Run the streamlit web application.

streamlit run app.py

3. After running above command a web page opens in your browser.
   Otherwise, Go to your browser and search the below url in address bar.

http://localhost:8501/

Techs

• Git & GitHub
• Python3.11
• Streamlit
• MongoDB
• Data Science libraries like pandas, numpy, matplotlib, seaborn, etc.

Features

• Predict the backorders in one click. I made the web app using streamlit which is a easy to easy tool to build a web app using python only.
• You can see the dataset analysis in Jupyter Notebook here.

Contributors