# Unsupervised Learning In this kind of learning, we do not have labeled training data. The most common unsupervised problem is **clustering**. There are also other unsupervised problems such as dimensionality reduction. Some applications of clustering include: * color quantization (16 million colors to 256 colors) * directed marketing (different ads for different groups of people) * pre-processing stage in supervised learning (in certain cases where it is clear that the examples are coming from well-defined groups) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://vikram-bajaj.gitbook.io/cs-gy-6923-machine-learning/main-4/types-of-machine-learning/unsupervised-learning.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.