Visualizing High-Dimensional Microbiome Data

To follow along, you can either download our Jupyter notebook here, or continue reading and typing in the following code as you proceed through the walkthrough. Unsupervised machine learning methods can allow us to understand and explore data in situations where we are not given explicit labels. One type of unsupervised machine learning methods falls under the family of clustering. Getting a general idea of groups or clusters of similar data points can inform us of any underlying structural patterns in our data, such as geography, functional similarities, or communities when we otherwise would not know this information beforehand. We will be applying our dimensional reduction techniques to Microbiome data acquired from UCSD's Qiita platform.