Recommender Systems
Movie recommender system built using various models
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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:
Demo
- Clone the Recommender_Systems
git clone https://github.com/kasuba-badri-vishal/Recommender_Systems.git
cd Recommender_Systems
- 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