K-Means Grouping Project

Objective

Create a K-Means grouping model that separates people into mixed and diverse groups. In this case, a model was built for people differing in age, skill, and proficiency. This was done by taking people from different clusterings in the k-means model.

Libraries and Languages

For the random data; Faker, CSV, NumPy, and Random, all in Python
For the k-means model; Pandas, NumPy, Kmodes, Kneed, and Datetime

Result

The K-means model grouped people into diverse groups, which was precisely what the model needed to do. It also can group people on group size.

Combined with the frontend on Wix, the following CSV file could be generated using the data from the k-means model.

This is the following result of the code above.