Michelin Restaurant Recommender

Group P

Members:
Ng Siong Kien (S2021587) Ku Muhammad Na'im bin Ku Khalif (S2016053) Wang Xin Li (S2000128) Kamyin Tang (S2019281)

Michelin Restaurant Recommender

Have you experienced of trying new cuisine but not knowing where to go? Have you been searching for a good restaurant in your area but cant find any?

Purpose

  • help to recommend restaurant suiting your preference
  • allow user to search nearby restaurant based on their location
  • one stop center of Michelin restaurant worldwide with price ranges

Who can use?

  • Anyone. Everyone. As long as you're food lover!

Dataset and Data Science Process

The Shiny app is built in R, and the recommendations are made by using the dataset provided by Kaggle:-
https://www.kaggle.com/jackywang529/michelin-restaurants Data Science Process

About the App

Feature

  • We covers up to 695 restaurants, 32 types of cuisines, 20 countries and totally 168 cities!
  • We covers all one star, two stars and three stars Michelin Restaurants!
  • Only need 5 inputs to get your preferred Michelin Restaurant!
  • Interactive map to search for the restaurant!
  • analysis available for you to explore further into the Michelin World!

An app that satisfy all your cravings! Let's try it out now!
Shiny App Link: https://ngsiongkien.shinyapps.io/MichelinRestaurantRecommender/

Summary of Experience

We have learned:-

  • how to ask question and resolve it
  • how to process the data and perform EDA using multiple libraries in RStudio
  • how to build a Shiny App and publish on RPub
  • how to build reproducible presentation using R Presentation

Main Reference: https://guide.michelin.com

R Code link:
https://github.com/ngsiongkien/shinyapp

Video link:
https://youtu.be/C7BQc25xHCs