Automated Machine Learning (AutoML) identifies and then executes the best algorithm fitting to each specific data set automatically with little or no human intervention. Expanding AutoML to clustering is gaining attention but facing additional hurdles due to the lack of ground-truth for model training. Making it work for market research is even more challenging because of the art part. But the value can be big. This research explores an automated system for market segmentation, shares learnings and novel solutions for future expansion.
