RikilG / Recommender_Systems

Recommender System to predict movie ratings

Recommender Systems

Movie recommender system built using various models
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Recommender_Systemsrt Bug · Request Feature

Table of Contents

• About the Project
• Getting Started
  • Prerequisites
  • Dependencies
  • Demo
• License
• Team Members
• Acknowledgements

About The Project

Information Retrieval Assignment - 3

This assignment is aimed at implementing and comparing various techniques for building a Recommender System.

Dataset used is from Movielens containing 1,000,209 anonymous ratings of approximately 3,900 movies made by 6,040 users. Get the dataset here

The code also ensures generous raters and strict raters are handled approximately

Built With Python

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

Python version > 3.4 is required to run this project properly

Dependencies

Following python modules are required:

• pandas
• numpy
• pickle

Demo

1. Clone the Recommender_Systems

git clone https://github.com/kasuba-badri-vishal/Recommender_Systems.git
cd Recommender_Systems

2. Run main.py

python main.py

License

Distributed under the MIT License. See LICENSE for more information.

Team Members

• Rohith Saranga - 2017A7PS0034H
• Kasuba Badri Vishal - 2017A7PS0270H
• Rikil Gajarla - 2017A7PS0202H

Acknowledgements

• We are grateful towards Prof. Aruna Malapati for providing us with this opportunity to work on this project