{"data":{"slug":"milvus-io-bootcamp","name":"bootcamp","tagline":"Dealing with all unstructured data including reverse image search, audio search, molecular search, video analysis, and question-answer systems.","github_url":"https://github.com/milvus-io/bootcamp","owner":"milvus-io","repo":"bootcamp","owner_avatar_url":"https://avatars.githubusercontent.com/u/51735404?v=4","primary_language":"Jupyter Notebook","stars":2443,"forks":684,"topics":["audio-search","deep-learning","embeddings","image-classification","image-recognition","image-search","llm","milvus","nlp","python","question-answering","rag","semantic-search","unstructured-data","vector-database"],"archived":false,"github_pushed_at":"2026-08-11T02:10:46+00:00","maintenance_label":"Active","stars_delta_30d":4,"url":"https://www.graphcanon.com/tools/milvus-io-bootcamp","markdown_url":"https://www.graphcanon.com/tools/milvus-io-bootcamp.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/milvus-io-bootcamp","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=milvus-io-bootcamp","description":"Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.","homepage_url":"https://milvus.io","license":"Apache-2.0","open_issues":0,"watchers":37,"ai_summary":"Milvus bootcamp repository focused on handling various types of unstructured data through deep learning techniques such as embeddings for tasks like image recognition/classification, NLP, semantic search, and more.","readme_excerpt":"<img src=\"pics/logo.png\" alt=\"milvus bootcamp banner\">\n\n<div class=\"column\" align=\"middle\">\n  <a href=\"https://github.com/milvus-io/bootcamp/blob/master/LICENSE\"><img height=\"20\" src=\"https://img.shields.io/github/license/milvus-io/bootcamp\" alt=\"license\"/></a>\n  <a href=\"https://milvus.io\"><img src=\"https://img.shields.io/badge/milvus-blue\" alt=\"milvus\"/></a>\n  <a href=\"https://cloud.zilliz.com/signup?utm_source=partner&utm_medium=referral&utm_campaign=2024-11-04_web_github-readme_global\"><img src=\"https://img.shields.io/badge/zilliz-green\" alt=\"fully-managed-milvus\"/></a>\n  <a href=\"https://milvus.io/slack\"><img src=\"https://img.shields.io/badge/Slack-%234A154B.svg?style=flat&logo=slack&logoColor=white\" alt=\"slack\"/></a>\n  <a href=\"https://discord.gg/mKc3R95yE5\"><img height=\"20\" src=\"https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white\" alt=\"discord\"/></a>\n  <a href=\"https://x.com/milvusio\"><img src=\"https://img.shields.io/twitter/follow/milvusio\" alt=\"twitter\"/></a>\n</div>\n\n## :bird: What You Can Do\n\nBegin an interactive journey to master [Milvus](https://milvus.io), enhancing your projects with seamless integration and optimization tools.\n\n- **Explore Tutorials:** Dive into notebooks that walk you through diverse Milvus use cases.\n\n- **Deploy Demos:** Build your own demo to see Milvus in action.\n\n- **Discover Use Cases:** Learn how Milvus integrates with other tools and frameworks through practical examples.\n\n- **Expand Your Skills:** Apply evaluation methods to test and optimize your applications.\n\n## :pencil: Examples\n\nYou can explore a comprehensive [Tutorials Overview](https://milvus.io/docs/tutorials-overview.md) covering topics such as Retrieval-Augmented Generation (RAG), Semantic Search, Hybrid Search, Question Answering, Recommendation Systems, and various quick-start guides. These resources are designed to help you get started quickly and efficiently.\n\n<table>\n  <tr>\n    <td width=\"30%\">\n      <a href=\"https://milvus.io/milvus-demos\">\n        <img src=\"https://assets.zilliz.com/image_search_59a64e4f22.gif\" />\n      </a>\n    </td>\n    <td width=\"30%\">\n<a href=\"https://milvus.io/milvus-demos\">\n<img src=\"https://assets.zilliz.com/qa_df5ee7bd83.gif\" />\n</a>\n    </td>\n    <td width=\"30%\">\n<a href=\"https://milvus.io/milvus-demos\">\n<img src=\"https://assets.zilliz.com/mole_search_76f8340572.gif\" />\n</a>\n    </td>\n  </tr>\n  <tr>\n    <th>\n      <a href=\"https://milvus.io/milvus-demos\">Image Search</a>\n    </th>\n    <th>\n      <a href=\"https://milvus.io/milvus-demos\">RAG</a>\n    </th>\n    <th>\n      <a href=\"https://milvus.io/milvus-demos\">Drug Discovery</a>\n    </th>\n  </tr>\n</table>\n\n\nHere is a selection of demos and tutorials to show how to build various types of AI applications made with Milvus:\n\n| Tutorial | Use Case | Related Milvus Features |\n| ----------- | -------- | -------- |\n| [Build RAG with Milvus](https://milvus.io/docs/build-rag-with-milvus.md) |  RAG | vector search |\n| [Advanced RAG Optimizations](https://milvus.io/docs/how_to_enhance_your_rag.md) | RAG | vector search, full text search |\n| [Full Text Search with Milvus](https://milvus.io/docs/full_text_search_with_milvus.md) | Text Search | full text search |\n| [Hybrid Search with Milvus](https://milvus.io/docs/hybrid_search_with_milvus.md) | Hybrid Search | hybrid search, multi vector, dense embedding, sparse embedding |\n| [Image Search with Milvus](https://milvus.io/docs/image_similarity_search.md) | Semantic Search | vector search, dynamic field |\n| [Multimodal Search using Multi Vectors](https://milvus.io/docs/multimodal_rag_with_milvus.md) | Semantic Search | multi vector, hybrid search |\n| [Movie Recommendation with Milvus](https://milvus.io/docs/movie_recommendation_with_milvus.md) | Recommendation System | vector search |\n| [Graph RAG with Milvus](https://milvus.io/docs/graph_rag_with_milvus.md) | RAG | graph search |\n| [Use Milvus as a LangChain Vector Store](https://milvus.io/docs/basic_usage_langch","github_created_at":"2019-08-09T10:00:06+00:00","created_at":"2026-07-07T17:44:06.905837+00:00","updated_at":"2026-08-21T12:00:48.850735+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"audio-search","name":"audio-search"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"embeddings","name":"embeddings"},{"slug":"image-classification","name":"image-classification"},{"slug":"image-recognition","name":"image-recognition"},{"slug":"image-search","name":"image-search"},{"slug":"llm","name":"llm"},{"slug":"milvus","name":"milvus"}],"trust":{"provenance":{"is_fork":false,"github_id":201441751,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T12:00:47.640Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":10,"last_release_at":"2025-05-22T07:39:23Z","stars_delta_30d":4,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:25:02.624Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T12:00:48.407Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-08-21T12:00:48.407Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-21T12:00:48.407Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- **When you need comprehensive integration guides**: Bootcamp offers detailed notebooks covering diverse use cases such as RAG, semantic search, hybrid searches, question answering systems, and video","image analysis.","- **For hands-on demos**: Build your own demonstrations to see Milvus in action through multiple examples provided by the tool. This is particularly useful for testing and understanding performance in","real-world applications."],"when_not_to_use":["- **When you want quick and minimal setup**: Bootcamp provides extensive integration possibilities but may require more setup effort compared to simpler tools, which could be a drawback if streamlined","operations are needed.","- **If focused on non-vector database solutions**: Since bootcamp is specific to Milvus and its wide array of vector search functionalities, it's less useful for those looking into other types of data","storage or processing that do not involve vector databases."],"source":"enrich:decision_facts","observed_at":"2026-07-09T08:49:12.362Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Interactive bootcamp for mastering Milvus use cases through tutorials and demos in areas like image search, audio search, molecular search, and more."}]}}