Movie Recommender System

This project was built as a part of Microsoft Engage 2022.

Table of Contents

1. About The Project
2. Features Implemented
3. Project Timeline
4. Built With
5. Instructions To Run
6. Video Demonstration
7. Additional Information

About The Project

A movie recommender web application, which gives personalized recommendations to users based on their rating history.

Users can also find recommendations by genre or by searching for a particular movie.

Features Implemented

1. Content-Based Recommendations
2. Collaborative Filtering Based Recommendations
3. Recommendations using IMDB's weighted rating formula
4. Search
5. Recommendations by Genre

Project Timeline

This project was built in 4 phases. The total time taken to complete this project was ≈ 3 weeks.

Built With

• Flask
• Pandas / Numpy
• Scikit-learn
• Bootstrap
• Select2
• SQLite

Instructions To Run

There are two ways to run this application. The simplest one is to use Docker.

1. Docker Installation

1. Install Docker for your system
2. Run the following command

docker run -p 5000:5000 sid2k3/movie_recommender:latest

Note: The recommender requires around 1 minute of one-time precomputation. Please wait while it completes this step.

2. Manual Installation

1. Install python 3.9
2. Clone this repository
3. Run the following command

python -m venv <venv_name>

4. Activate the virtual environment

In CMD / Windows

<venv_name>\Scripts\activate.bat

In Bash / Linux

source <venv_name>/bin/activate

5. Install the dependencies

pip install -r requirements.txt

6. Start the server

python main.py

Note: The recommender requires around 1 minute of one-time precomputation. Please wait while it completes this step.

Demonstration Video

To view the video click here.

Additional Information

To know more about this project click here.