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a java + Python hybrid intelligent recommendation system applying machine learning and modular archuitecture

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Smart Recommendation System

A data-driven platform for product recommendation, analytics, and user behavior insights. This project integrates Java (Spring Boot), PostgreSQL, MongoDB, and a data science workflow to generate personalized recommendations and provide an analytical dashboard.


🚀 Features

🔐 JWT Authentication

🧠 Product Recommendation Engine

🗄️ PostgreSQL for relational data

🍃 MongoDB for product metadata and logs

🔌 REST API for front-end integration

📊 Admin dashboard with analytics

🔄 ETL and data preprocessing pipeline


🧰 Tech Stack

Layer Technology
Back-end Java 17, Spring Boot
Database PostgreSQL, MongoDB
Security JWT, Spring Security
Data Science Python, Pandas, Jupyter Notebook
Deployment Docker, Docker Compose
Documentation Markdown + Mermaid Diagrams

📁 Project Structure

smart_recommendation-system/ │── src/ │ ├── main/java/... │ ├── main/resources/ │ └── test/ │── docker/ │── notebooks/ │── scripts/ │── README.md │── docker-compose.yml │── pom.xml


🏁 Getting Started git clone https://github.com/Kaua19/smart_recommedation-system cd smart_recommedation-system

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a java + Python hybrid intelligent recommendation system applying machine learning and modular archuitecture

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