A visualization of restaurant ratings using machine learning and the Yelp academic dataset
This is the second project from UC Berkeley's CS61a class (The Structure and Interpretation of Computer Programs)
Here is a link to the class website: http://cs61a.org/ Here is a link to the project description: http://cs61a.org/proj/maps/
The only files modified in this project are utils.py, abstractions.py, and recommend.py
Here is some information from the class website on the project: In this project, you will create a visualization of restaurant ratings using machine learning and the Yelp academic dataset. In this visualization, Berkeley is segmented into regions, where each region is shaded by the predicted rating of the closest restaurant (yellow is 5 stars, blue is 1 star). Specifically, the visualization you will be constructing is a Voronoi diagram.
In the map above, each dot represents a restaurant. The color of the dot is determined by the restaurant's location. For example, downtown restaurants are colored green. The user that generated this map has a strong preference for Southside restaurants, and so the southern regions are colored yellow.