6) UNSUPERVISED ML

As automation advances, more and more non-human data science solutions are required. Unsupervised machine learning is a trend with potential for many different sectors and use situations. We already understand from earlier methods that computers cannot learn in a vacuum. For the solution they offer, they must be able to take fresh information and analyze it.

Input that data into the system, however, usually calls for human data scientists. ML that is not supervised focuses on unlabeled data. Unsupervised machine learning programs must make their own decisions without the assistance of a data scientist.

This can be used to swiftly analyze data structures, find patterns that can be of help, and then use this knowledge to enhance and further automate decision-making. netizenstechnologies.com