--- title: A Beginner’s Guide to Vector Embeddings | daily.dev description: Vector embeddings are compact representations of data that capture structural or semantic relationships. They are used in various AI applications and can be... canonical: https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: A Beginner’s Guide to Vector Embeddings | daily.dev og:description: Vector embeddings are compact representations of data that capture structural or semantic relationships. They are used in various AI applications and can be... og:url: https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn og:image: https://api.daily.dev/og/posts/GLJthHdRn.png og:image:alt: A Beginner’s Guide to Vector Embeddings og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # A Beginner’s Guide to Vector Embeddings **[TigerData \(Creators of TimescaleDB\)](https://daily.dev/sources/tigerdata)** · 13 min read · 5 upvotes · 0 comments ## Summary Vector embeddings are compact representations of data that capture structural or semantic relationships. They are used in various AI applications and can be created using neural networks. Different types of vector embeddings exist for different kinds of data. To create vector embeddings for your data, you can use embedding models or APIs. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#embeddings](https://daily.dev/tags/embeddings), [#neural-networks](https://daily.dev/tags/neural-networks) [View this post on daily.dev](https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"A Beginner’s Guide to Vector Embeddings","url":"https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn"},"datePublished":"2024-04-29T18:26:21.060Z","dateModified":"2024-07-02T02:15:38.281Z","description":"Vector embeddings are compact representations of data that capture structural or semantic relationships. They are used in various AI applications and can be...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/9023909348abce6510d436706845c604?_a=AQAEuiZ","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/9023909348abce6510d436706845c604?_a=AQAEuiZ","isAccessibleForFree":true,"articleSection":"TigerData (Creators of TimescaleDB)","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"TigerData (Creators of TimescaleDB)","logo":"https://media.daily.dev/image/upload/s--bsnY3goS--/f_auto/v1756960371/squads/timescale?_a=BAMClqZW0","url":"https://daily.dev/squads/tigerdata"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/a-beginner-s-guide-to-vector-embeddings-gljthhdrn","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":5},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"embeddings,neural-networks","timeRequired":"PT13M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"TigerData (Creators of TimescaleDB)","item":"https://daily.dev/squads/tigerdata"},{"@type":"ListItem","position":3,"name":"A Beginner’s Guide to Vector Embeddings"}]} ```