A data science blog
To follow up my two previous posts where I analysed ingredient lists and ratings for dessert recipes, I decided to make a Shiny app to explore the data interactively. You can find the app here. (As a quick aside, to deploy my Shiny app on AWS I relied heavily on Charles Bordet’s excellent and comprehensive guide.) You can select an ingredient either by clicking a point on the plot or by selecting it from the dropdown. Read More…
In a previous post, I explored ingredient lists from dessert recipes from the website taste.com.au. In this post, I’ll be using that dataset to identify ingredients that influence a recipe’s rating (whether negatively or positively). As a reminder, my main questions are: How well does ingredient composition predict the rating of a recipe? Which individual ingredients contribute to high and low scores? Which combinations of ingredients contribute to high and low scores? Read More…
If you enjoy cooking, you might be familiar with a book called the Flavour Bible. You can look up an ingredient and find lists of other ingredients that go well with it, with an emphasis on interesting or unusual combinations. It’s an amazing resource for discovering creative combinations of ingredients. In this series of posts, I’ll try to create something similar using a dataset of ingredient lists and their ratings. Read More…