Yelp_Rating_Regression_Predictor

The restaurant industry is tougher than ever, with restaurant reviews blazing across the internet from day one of a restaurant's opening. Since a restaurant's success is highly correlated with its reputation, in this project, I'll discover what makes a restaurant gets the best reviews on the most queried restaurant review site, Yelp. With a dataset of different restaurant features and their Yelp ratings, I will load, merge, clean, analyze the data and then use a Multiple Linear Regression model to investigate what factors most affect a restaurant's Yelp rating.

In this project I'll be working with datasets provided by Yelp:

• yelp_business.json: establishment data regarding location and attributes for all businesses in the dataset
• yelp_review.json: Yelp review metadata by business
• yelp_user.json: user profile metadata by business
• yelp_checkin.json: online checkin metadata by business
• yelp_tip.json: tip metadata by business
• yelp_photo.json: photo metadata by business

For detailed explanation of the features in each .json file, see the accompanying feature_descriptions.