📊 Personalized Product Recommendation System

(This project is part of the Flipkart Grid 2023 Hackathon and was selected for the finals)

This repository contains a Flask-based web application that provides personalized product and brand recommendations for users. The application loads user and brand data, processes it with trained neural network models, and displays top recommendations based on the user's preferences.

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Table of Contents

• Features
• Setup Instructions
• How to Run
• How to Use
• Datasets
• Project Structure

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Features

• User and Brand Recommendations: Provides product recommendations for a selected user and brand recommendations based on product popularity and brand attributes.
• Interactive Interface: Users can select desired user and brand options for recommendations.
• Data-Driven Models: Utilizes pre-trained neural network models to generate personalized recommendations.

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Setup Instructions

1. Clone the Repository:

   git https://github.com/guneeshvats/Personalised-Product-Recommendation-System.git
   cd your-repository
   

2. Install Dependencies

   pip install -r requirements.txt
   

🚀 How to Run

1. Prepare Datasets: Ensure all required datasets are in the same directory as app.py.
2. Start the Application:

   python3 app.py
   
   

📝 How to Use the Application Select User Data: Use the dropdown menu to choose the specific user whose data you want to visualize. Select Brand Data: For brand-specific analysis, select both the user and the brand name from the dropdown options. With a few clicks, you can easily navigate between user and brand visualizations for an insightful data exploration experience!

The datasets required for this application can be found here:

https://drive.google.com/drive/folders/1f3PhKi-p8I7afQvr2dIymALAGF2QyVVE?usp=sharing