Machine Learning Clustering is an unsupervised machine learning method where data points are group with each other based on their similarity.

Most importantly,  data are not labeled, and we have no idea what our results should look like. 

Clustering is a very useful machine learning technique and has been applied in a wide range of industries.  For example:

• Customer Segmentation: Customers are categorized by using clustering algorithms according to their purchasing behavior or interests to develop focused marketing campaigns. 
• Product segmentation: Products are categorized by using clustering algorithms according to their design characteristics, sales and supply  behavior or interests to form forecast units for demand forecasting. 
• Inventory segmentation: Parts are categorized by using clustering algorithms according to their sourcing and purchasing behavior to develop inventory strategies and policies.  

Clustering is not as straightforward as supervised machine learning algorithms. It is mostly because it is not possible to pre-defined the performance.  As a result, it requires domain expertise and human judgment to decide whether the results are desirable or not.