This is a food recommendation notebook. It uses the datasets from the following link, one of which is included which is the Grocery and Gourmet ratings data. It has different users, the products they reviewed, and what rating they gave them. Our application supports other data sets from this site as well, with some slight modifications to the notebook.
http://jmcauley.ucsd.edu/data/amazon/
This application takes a new product that a person likes, and uses the Pearson Correlation Score algorithm to find out which other foods the person may like.
To run, open the python notebook, run each step, and then at the very last line, put in a product ID from the top 100 products. It will then tell you which other products you may like. You can search the product ID on Google, and find Amazon link to know what it is. You can also look at the html file if you don't want to run the notebook or don't have Jupyter installed.