recommendation_system

expo project

sample output:

Event Recommendation System

This repository contains an Event Recommendation System that leverages machine learning models to predict event names based on student profiles and event attributes. Built with Python, Streamlit, and scikit-learn, this app aims to enhance event suggestions for students based on their academic and demographic attributes.

Features

• Interactive UI: Built with Streamlit for ease of use.
• Machine Learning Models: Uses RandomForestClassifier and KNeighborsClassifier to recommend events.
• Data Processing: Encodes categorical variables and merges data to create comprehensive student-event profiles.
• Real-time Predictions: Suggests event names based on input features.

Installation

Prerequisites

• Python 3.8 or higher
• Recommended: VS Code or Jupyter Notebook

Clone the Repository

Clone this repository and navigate to the project folder:

git clone https://github.com/raak-16/recommendation_system.git
cd recommendation_system
pip install -r requirements.txt


Usage
To launch the Streamlit app:

streamlit run streamy.py