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Book Overview & Buying
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Table Of Contents
The Definitive Guide to OpenSearch
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This chapter introduced key concepts and usage patterns for vector search with OpenSearch. You learned about the fundamentals of sparse and dense vectors and how they represent information, including contextual information. You learned about quantization techniques that reduce latency and memory footprint, trading off cost for accuracy. You employed OpenSearch’s FAISS engine to use the HNSW and IVF algorithms for vector storage and retrieval. Finally, you implemented a retrieval-augmented generation chatbot, with conversational memory in OpenSearch.
Congratulations! You now have all of the keys to build your search application. In the next and following chapters, we’ll dive deep into operational topics such as migrating to OpenSearch, security, monitoring, and optimizing your deployment.
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