Unsupervised machine learning is a type of machine learning that uses unlabeled data. It is not possible to provide a label for the data as it is collected. This method can be used in fields like medical research where there is no prior knowledge about the outcome of an experiment.
Supervised machine learning, on the other hand, uses labeled data which are pre-existing and known beforehand.
Unsupervised machine learning is a type of machine learning in which the algorithm does not have any pre-defined input/output pairs. Unsupervised machine learning has been used to explore and model complex data sets. They are also used for tasks like image classification and text analysis.
The benefits of using unsupervised machine learning are that it can help you focus on your problem and make sure you don't spend time on things that aren't relevant to your problem. The algorithm will use this information to generate insights and recommendations for your business, and it can also help you find patterns in your data that might not have been obvious without the help of AI.