# Types of ML Problems ### Classification Given an input, predict what class it is in (discrete). Examples: * Given a picture of a handwritten letter, predict what letter it actually is * Given the previous 10 days of weather, predict how the sky will be (clear, cloudy, partly cloudy, etc) * Given a chess board, predict which move a player should make next ### Regression Given an input, predict a numerical value (continuous). Examples: * Estimating stock prices * Estimating the tomorrow's temperature * Estimating how long it will take you to drive somewhere ### Clustering Given unlabeled data, cluster them into natural groups. Examples: * Identifying close friend groups on Facebook * Generating common groups of people on Spotify based on their music tastes ## Practice Based on the above, what do you think Netflix show recommendations use? It's not obvious, nor is it just one of them :) --- # 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://15-112.gitbook.io/machine-learning/machine-learning-common-algorithms/types-of-ml-problems.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.