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Build a Vector Search Engine in Python with FAISS and Sentence Transformers
This story was originally published on HackerNoon at: https://hackernoon.com/build-a-vector-search-engine-in-python-with-faiss-and-sentence-transformers.
Learn how to build a production grade vector search engine from scratch using Python, Sentence Transformers and FAISS.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #vector-search, #building-ai-infra, #vector-embedding, #faiss, #sentence-transformers, #rag-systems, #ai-search-engines, #faiss-tutorial, and more.
This story was written by: @ksurya220. Learn more about this writer by checking @ksurya220's about page,
and for more stories, please visit hackernoon.com.
This tutorial walks through building a semantic vector search engine from scratch using Python, Sentence Transformers, and FAISS. You’ll learn how embeddings work, how similarity search is performed, and how modern AI systems retrieve relevant information at scale. By the end, you’ll have a working vector search engine and a deep understanding of the infrastructure behind LLM-powered applications, RAG systems, and semantic search.
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By HackerNoon
5
11 ratings
This story was originally published on HackerNoon at: https://hackernoon.com/build-a-vector-search-engine-in-python-with-faiss-and-sentence-transformers.
Learn how to build a production grade vector search engine from scratch using Python, Sentence Transformers and FAISS.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #vector-search, #building-ai-infra, #vector-embedding, #faiss, #sentence-transformers, #rag-systems, #ai-search-engines, #faiss-tutorial, and more.
This story was written by: @ksurya220. Learn more about this writer by checking @ksurya220's about page,
and for more stories, please visit hackernoon.com.
This tutorial walks through building a semantic vector search engine from scratch using Python, Sentence Transformers, and FAISS. You’ll learn how embeddings work, how similarity search is performed, and how modern AI systems retrieve relevant information at scale. By the end, you’ll have a working vector search engine and a deep understanding of the infrastructure behind LLM-powered applications, RAG systems, and semantic search.