jaren0702 / bootcamp

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Report Bug or Request Feature

Reverse Image search	Chatbots	Chemical structure search

Table of Contents

1. About Milvus Bootcamp
2. Solutions
   • Run locally
   • Live demo
3. Benchmark Tests
4. Contributing
5. Supports

📣 About Milvus Bootcamp

Embed everything, thanks to AI, we can use neural networks to extract feature vectors from unstructured data, such as image, audio and vide etc. Then analyse the unstructured data by calculating the feature vectors, for example calculating the Euclidean or Cosine distance of the vectors to get the similarity.

Milvus Bootcamp is designed to expose users to both the simplicity and depth of the Milvus vector database. Discover how to run benchmark tests as well as build similarity search applications like chatbots, recommender systems, reverse image search, molecular search, video search, audio search, and more.

📝 Solutions

🍦 Run locally

Here are several solutions for a wide range of scenarios. Each solution contains a Jupyter Notebook or a Docker deployable solution, meaning anyone can run it on their local machine. In addition to this there are also some related technical articles and live streams.

And more solutions you can refer to the Examples.

You can also refer to the Bootcamp FAQ for troubleshooting.

Solutions	Have fun with it	Article	Video
Reverse Image Search Build a reverse image search system using Milvus paired with Towhee for feature extraction.	- Jupyter notebook - Quick deploy	- 10 行代码搞定以图搜图 - Building a Search by Image Shopping Experience with VOVA and Milvus	- 中文
Text Image Search Search for matched or related images given an input text by Milvus and Towhee.	- Jupyter notebook	- 从零到一，教你搭建「CLIP 以文搜图」搜索服务（一） - 从零到一，教你搭建「CLIP 以文搜图」搜索服务（二）：5 分钟实现原型
Question Answering System Build an intelligent chatbot using Milvus and Towhee for natural language processing (NLP).	- Jupyter notebook - Quick deploy	-快速搭建对话机器人，就用这一招！ -Building an Intelligent QA System with NLP and Milvus	-中文
	-PaddlePaddle(QA 中文) -PaddlePaddle(FAQ 中文)
Text Search Engine Build a text search engine using Milvus and BERT model.	- Jupyter notebook	- Milvus 实战 | Milvus 与 BERT 搭建文本搜索	- 中文
	- PaddlePaddle(中文)
Recommender System Build an AI-powered movie recommender system using Milvus paired with PaddlePaddle’s deep learning framework.	- Jupyter notebook	- 强强联手！Milvus 与 PaddlePaddle 深度整合，赋能工业级 AI 应用
Video Similarity Search Build a video similarity search engine using Milvus and Towhee.	- Jupyter notebook	- Milvus实战｜ 以图搜视频系统 - Building a Video Analysis System with Milvus Vector Database
Video Deduplication Build a video deduplication system to detect copied video sharing duplicate segments.	- Jupyter notebook
Text Video Search Search for matched or related videos given an input text by Milvus and Towhee.	- Jupyter notebook	- 5分钟实现「视频检索」：基于内容理解，无需任何标签
Audio Classification Build an audio classification engine using Milvus & Towhee to classify audio.	- Jupyter notebook
Audio Fingerprinting Build engines based on audio fingerprints using Milvus & Towhee, such as music detection system.	- Jupyter notebook
Molecular Similarity Search Build a molecular similarity search system using Milvus paired with RDKit for cheminformatics.	- Jupyter notebook	- Milvus 赋能 AI 药物研发	- 中文

🎬 Live Demo

We have built online demos for reverse image search, chatbot and molecular search that everyone can have fun with.

🔍 Benchmark Tests

The VectorDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison.

📝 Contributing

Contributions to Milvus Bootcamp are welcome from everyone. See Guidelines for Contributing for details.

🔥 Supports

Join the Milvus community on Slack to give feedback, ask for advice, and direct questions to our engineering team. We also have a WeChat group.