pick-n-chill

🎥 Movie recommendation tool

A movie recommendation tool built with the help of Machine Learning (content-based recommender system). Ever take too much time trying to find similar movies? Search up a movie on our site and get recommended with simlar movies to match your taste!

PS: We built this project to practice our skills.

Table of Contents

• Team
• Tech Stack
• Setup Locally
  • Backend server
  • Frontend
• Screenshots
• License

Team

• @hk2257853: Backend
• @Greeshma2903: Design, Frontend
• @Pratham-cymk: Machine Learning

Tech Stack

• Client: React, WindiCSS, React Router
• Server: Node, Express
• ML : scikit learn, Pandas (Python)

API Used

• The Movie Database: https://developers.themoviedb.org/3/getting-started/introduction

Setup Locally

• Run the commands in your terminal/command line.
• Requirements: python3, pip, npm (nodejs)

1. Clone or download the repo on your local system, and navigate to the project directory.

   git clone https://github.com/Greeshma2903/movie-recommendation-system.git && cd movie-recommendation-system

For the ML Model and Node server

2. Navigate to server directory

   cd 'server'

3. Setup the virtual environment to install the python packages

   Virtualenv is a tool to set up your Python environments. (read this for installation)

   # install virtual environment to your host python, if you haven't already:
      # pip install virtualenv
      # OR
      # python -m pip install virtualenv
   
   # use the virtual env
   python<version> -m venv env
   # example
   python3 -m venv env

   To activate the virual environment:

   # on mac or linux
   source env/bin/activate
   
   # on windows
   env/Scripts/activate.bat # in CMD line
   env/Scripts/Activate.ps1 # in Powershell

4. Install all the libraries mentioned in the requirements.txt file with the command:

   pip install -r requirements.txt
   
   # OR
   python -m pip install -r requirements.txt

5. Dectivate the environment after you're done with your work:

   deactivate

6. For the project to work, you need get your API key from TMDB's website, and store it in a .env file in the server folder.

   # .env file
   API_KEY=###

7. To run the node server

   npm install
   npm start

Client

1. Go to the project directory

   cd client

2. Install dependencies

   npm install

3. Run the server at localhost

   npm run dev

Screenshots

click here

License

MIT