Unsupervised ML

Unlike Supervised ML, does not require labelled training data.

It can be used for two types of problems:

• Clustering groups based on similarity
• Association which looks for relationships between variables

Examples

• Clustering customers based on behaviours
• Segmenting images
• Identifying topics in document