RecSys: Recommendation System Project

This repository contains a recommendation system project implemented using collaborative filtering techniques.

Project Overview

This project aims to develop a recommendation system using collaborative filtering methods. The system is designed to provide personalized recommendations based on user preferences and item similarities.

Features

• Collaborative Filtering: Implements both user-based and item-based collaborative filtering algorithms.
• Data Preprocessing: Includes scripts for cleaning and preparing the input data.
• Evaluation Metrics: Incorporates various metrics to assess the performance of the recommendation system.

Getting Started

Prerequisites

• Python 3.7+
• pandas
• numpy
• scikit-learn Installation Clone the repository:

git clone https://github.com/Huvinesh-Rajendran-12/recsys.git

Install the required dependencies:

pip install -r requirements.txt

Usage

Prepare your data in the required format (CSV file with user, item, and rating columns). Run the data preprocessing script:

python preprocess_data.py

Train the recommendation model:

python train_model.py

Generate recommendations:

python generate_recommendations.py