Awesome

A Culinary Tour of Data Science

Analyzing the Epicurious recipe data available on Kaggle using network science and graph theory.

Prerequisites

• nltk 3.4.5
• networkx 2.3
• numpy 1.16.5
• pandas 0.25.1
• seaborn 0.9.0

File descriptions

Data Processing and Graph Construction.ipynb - uses natural language processing techniques to extract ingredients from a raw recipe text for each dish and then builds a weighted graph with nodes being dishes and connects them based on the common ingredients they share using Jaccard simialrity index

Exploring the Graph.ipynb - explores the structure and various properties of the graph

Data Exploitation.ipynb - this is the main notebook which tries to answer the research questions. It includes the following:

• Network visualizations
• Clustering using Louvain method (community detection)
• KNN-based recommender system
• Logistic regression model predicting recipe ratings using graph filtering