QMT=9{P#=R&2{4={}Q8)|}$9AR|
SYSTEM PROCESSING...
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SYSTEM PROCESSING...
Posted: 2025-04-13 17:41:28 UTC
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
Status
Last Updated
2025-04-13 17:42:26 UTC
Verified By
Rollup News
This course teaches how to optimize Retrieval-Augmented Generation (RAG) using MongoDB, focusing on techniques like vector search, metadata filtering, projections, boosting, and prompt compression to improve performance and reduce costs.
Vector search for semantic matching
Metadata filtering to narrow search results
Projections to minimize data returned
Boosting to improve relevance
Prompt compression to reduce token count and costs
Scaling RAG applications
Performance issues in large-scale RAG
Security challenges in RAG