This exercise uses some unsupervised machine learning techniques. It involves:
- Normalise data using the scikit-learn StandardScaler module.
- Use the elbow method algorithm to find the best value for k using the Original Data
- Cluster the data with K-Means by using the original data
- Optimise the clusters with principal component analysis (PCA) where n-components = 3
- Find the best value for k by using the PCA data
- Cluster the data with K-Means by using the PCA data
- Visualise and compare the results