Part of the Machine Learning Nanodegree Program.
Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
- Clustering
- sklearn
- PCA/ICA
- Visualizing Data
- Feature Selection