Wine Recommender System

a web recommender tutorial using Python, Django, and Pandas.

This repository contains the code for such a web application in different stages as git tags.

• stage-0: an empty repo.
• stage-0.1: a Django project with one app called reviews. The app defines model entities.
• stage-0.2: admin site up and running for our model entitities Wine and Review.
• stage-0.3: views and templates are available.
• stage-0.4: add review form added.
• stage-0.5: template reuse.
• stage-1: added Bootstrap 3 for Django.
• stage-1.1: add_review now requires login. Added login templates and menu sesion links.
• stage-1.2: a user reviews page created.
• stage-2: user management done.
• stage-2.1: Scripts to load CSV available + data loaded.
• stage-2.2: An empty wine suggestions view has been added.
• stage-2.3: Suggestions view now shows wines not reviewed by the user.
• stage-2.4: Added cluster model object and manually created three clusters.
• stage-2.5: Suggestions view now makes use of cluster information.
• stage-3: K-means clustering based recommendations provided.

Tutorials

The following tutorials will guide you through each of the previous Git tags while learning different concepts of data product development with Python.

A Wine Review Website using Django and Bootstrap

Adding User management

Providing wine recommendations using K-Means