{"version":"1.0","type":"card","id":"dd7706f5-9568-41c4-a8ff-40a29b6fb2e5","url":"https://stacklist.com/card/dd7706f5-9568-41c4-a8ff-40a29b6fb2e5","title":"Reservoir Sampling","source_url":"https://samwho.dev/reservoir-sampling/?utm_campaign=Data_Elixir&utm_source=Data_Elixir_534","note":"Learn how to make random selections from a population whose size is unknown. This algorithm, called reservoir sampling, provides a fair chance of choosing each item despite the unknown population size.","image":{"url":"https://ucarecdn.com/044b6988-ec59-45fd-b90f-6a00dc1f33b9/","alt":"Reservoir Sampling","width":1200,"height":630},"stack":{"id":"2183a3b7-294a-4aad-9c4f-5baf7d2f9a64","title":"statsy","url":"https://stacklist.com/c/education/stack/2183a3b7-294a-4aad-9c4f-5baf7d2f9a64"},"created_at":"2025-05-16T04:00:25.362Z","updated_at":null,"aco":{"summary":"This website explains the concept of reservoir sampling, a technique used to select a fair random sample from a dataset when the size of the dataset is unknown. It explains how it works using examples and illustrations, and covers both selecting single and multiple items from the dataset. It also demonstrates how it can be applied to real-world scenarios such as log collection. \n","tags":[],"key_entities":[],"classification":null,"language":null,"confidence":null,"provenance":null,"token_counts":{"approximate":107},"content_hash":null,"acp_version":"0.2","body_available":false,"body_tokens":0,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/dd7706f5-9568-41c4-a8ff-40a29b6fb2e5.json","html":"https://stacklist.com/card/dd7706f5-9568-41c4-a8ff-40a29b6fb2e5","md":"/api/public/card/dd7706f5-9568-41c4-a8ff-40a29b6fb2e5.md","stack_json":"/api/public/stack/2183a3b7-294a-4aad-9c4f-5baf7d2f9a64.json"}}