Skip to content

Latest commit

 

History

History
122 lines (58 loc) · 3.23 KB

README.md

File metadata and controls

122 lines (58 loc) · 3.23 KB

Movie-Recommendation-System ⭐️ ⭐️ ⭐️

A Machine Learning Project Movie Recommendation system using React and Flask.

In this Web application i used React for Front-end and Flask for Back-end.

For Movie-Recommendation i have used Machine Learning model which is trained over tmdb 5000 Movie dataset and provide the Recommendation

I used COSINE SIMILARITY algorithm to get similarity when user chooses a movie .

Features ⭐️

1.User can Search Movie

2.User can watch trailer and some clips of the Movie

3.If a user watched a clips of a movie then the movie details will stored in localstorage and based on the movie name the user will see the recommendation on the home screen

4.If a user type a text in Searchbar then it will auto complete.

Screenshots ⭐️

Mobile View:

App Screenshot

App Screenshot

App Screenshot

Desktop View:

App Screenshot

App Screenshot

App Screenshot

App Screenshot

Run Locally ⭐️

Clone the project

https://github.com/msubham193/movie-recommender-system.git

to run fron-end

  cd movie-app

Install dependencies

   npm install

Start the server

   npm start

to run backend

   cd server

Install dependencies

   pip3 install -r requirements.txt

Start the server

   python3 app.py

Demo ⭐️

https://storied-gumption-54deb8.netlify.app/

Documentation ⭐️

Flask =====> Click here

Cosine Similarity =====> Click here

Tailwindcss =====> Click here

Tech Stack ⭐️

React,TailwindCSS,Flask,Machine Learning