Question 32: What is unsupervised learning?Answer: Neither feature nor number of groups is known

Unsupervised learning is a type of machine learning that looks for previously undetected patterns in a data set with no pre-existing labels and with a minimum of human supervision. In contrast to supervised learning that usually makes use of human-labeled data, unsupervised learning, also known as self-organization allows for modeling of probability densities over inputs.

It's called "unsupervised" because unlike supervised learning, where the data is already labeled and the algorithm learns to predict the output from the input data, unsupervised learning does not have labeled data provided. Instead, the algorithm must figure out what is being shown on its own.

The goal of unsupervised learning is to find the underlying structure of dataset, group the data into different categories, or represent the data in a new way. Common unsupervised learning techniques include clustering, dimensionality reduction, and anomaly detection.