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코드 따라하기 ↗Semantic Search with Pinecone
Learn the fundamentals of text embedding and vector databases with Pinecone to build a simple search engine.
James Briggs
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Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.관련

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Vector databases enable semantic search - searching on the meaning of the text - to provide higher quality results than traditional keyword search. In this project, you'll learn how to use Pinecone, a popular vector database platform, to do this. You'll start by setting up a developer account with Pinecone and integrating it with DataLab (fka Workspace), and learn how to "embed text" and import it into Pinecone, before using it for search. You'll also learn about embedding dimensions, distance metrics, and other concepts to control the performance of the results.