--- title: A Complete Noobs Guide to Vector Search, Part 1 | daily.dev description: A two-part guide to vector search covering topics such as converting text data into vectors, embedding, vector representation, similarity metrics, and the HNSW... canonical: https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: A Complete Noobs Guide to Vector Search, Part 1 | daily.dev og:description: A two-part guide to vector search covering topics such as converting text data into vectors, embedding, vector representation, similarity metrics, and the HNSW... og:url: https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne og:image: https://api.daily.dev/og/posts/MP7VnDKnE.png og:image:alt: A Complete Noobs Guide to Vector Search, Part 1 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 Complete Noobs Guide to Vector Search, Part 1 **[Collections](https://daily.dev/sources/collections)** · 1 min read · 3 upvotes · 0 comments ## Summary A two-part guide to vector search covering topics such as converting text data into vectors, embedding, vector representation, similarity metrics, and the HNSW algorithm. ## Content Welcome to the Complete Noobs Guide to Vector Search! In this two-part series, we will cover everything you need to know about vector search and how to use it effectively. Part 1 will focus on the process of converting text data into vectors. We will discuss topics such as tokenization, embedding, and vector representation. Additionally, we will provide step-by-step instructions on how to embed and upsert data into Qdrant, a powerful vector database. In Part 2, we will delve into the concept of vector search itself. You will learn about similarity metrics and the HNSW algorithm, which is used for efficient searching through vector databases. If you're new to vector search or just want to brush up on your knowledge, this guide is perfect for you. Let's get started! ## Similar posts on daily.dev - [Don’t just attend KubeCon \+ CloudNativeCon, Merge Forward your experience\!](https://daily.dev/posts/don-t-just-attend-kubecon-cloudnativecon-merge-forward-your-experience--l0rpp73x8) · CNCF · 1 upvotes · 0 comments - [Announcing H2 2026 KCDs](https://daily.dev/posts/announcing-h2-2026-kcds-m96goajm1) · CNCF · 1 upvotes · 0 comments - [Two months of Open Community Groups](https://daily.dev/posts/two-months-of-open-community-groups-asf52zhbs) · CNCF · 0 upvotes · 0 comments - [CNCF Unveils Schedule for KubeCon \+ CloudNativeCon Europe 2026](https://daily.dev/posts/cncf-unveils-schedule-for-kubecon-cloudnativecon-europe-2026-ikhcoa5cb) · CNCF · 2 upvotes · 0 comments - [CNCF Debuts KubeCon \+ CloudNativeCon Japan 2026 Schedule](https://daily.dev/posts/cncf-debuts-kubecon-cloudnativecon-japan-2026-schedule-xp5pyudub) · CNCF · 1 upvotes · 0 comments --- Tags: [#embeddings](https://daily.dev/tags/embeddings), [#vector-search](https://daily.dev/tags/vector-search) [View this post on daily.dev](https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne) ```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 Complete Noobs Guide to Vector Search, Part 1","url":"https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne"},"datePublished":"2024-04-30T13:46:29.678Z","dateModified":"2024-07-02T02:15:08.796Z","description":"A two-part guide to vector search covering topics such as converting text data into vectors, embedding, vector representation, similarity metrics, and the HNSW...","image":"https://miro.medium.com/v2/resize:fit:700/1*Wl6OxKf6K2WEoVSczkFlIQ.gif","thumbnailUrl":"https://miro.medium.com/v2/resize:fit:700/1*Wl6OxKf6K2WEoVSczkFlIQ.gif","isAccessibleForFree":true,"articleSection":"Collections","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":"Collections","logo":"https://media.daily.dev/image/upload/s--fk_6ycEi--/f_auto,q_auto/v1780996001/logos/collections?_a=BAMAMiWQ0","url":"https://daily.dev/sources/collections"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/a-complete-noobs-guide-to-vector-search-part-1-mp7vndkne","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"embeddings,vector-search","timeRequired":"PT1M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Collections","item":"https://daily.dev/sources/collections"},{"@type":"ListItem","position":3,"name":"A Complete Noobs Guide to Vector Search, Part 1"}]} ```