Welcome to the Kmeans clustering Workshop as part of the Data Science with Python Series. In this workshop we will cover the basics of implementing a kmeans clustring algorithm, how to choose the optimal number of clusters and how to evaluat the clusters that you end up with.
Author: Philip Wilkinson, Head of Science (21/22) UCL Data Science Society (philip.wilkinson.19@ucl.ac.uk)
Prior to this lecture please install
Proudly presented by the UCL Data Science Society
├── DS - Data Science with Python - Kmeans clustering
│ ├── README.md
│ ├── Data
│ │ ├── Convenience_stores_dataset.gpkg
│ │ ├── London_outline.gpkg
│ ├── problem.ipynb
│ ├── solution.ipynb
└── workshop.ipynb