PyImageSearch

MAY 19, 2025

In this tutorial, well explore how OpenSearch performs k-NN (k-Nearest Neighbor) search on embeddings. How OpenSearch Uses Neural Search and k-NN Indexing Figure 6 illustrates the entire workflow of how OpenSearch processes a neural query and retrieves results using k-Nearest Neighbor (k-NN) search.

K-nearest Neighbors 91

K-nearest Neighbors AWS Deep Learning Deep Learning 91

Flipboard

MAY 5, 2025

Vector and Semantic Search: Leverages machine learning-powered search techniques, including k-NN (k-nearest neighbors) and dense vector embeddings, for applications like AI-driven search, recommendation systems, and similarity search. Learning to Rank (LTR) and Re-Ranking: Uses ML models (e.g., What's next?

AWS 116

AWS Clustering Deep Learning Deep Learning 116

PyImageSearch

MAY 12, 2025

Powering Neural Search : Enables advanced similarity-based retrieval using OpenSearchs k-NN (k-Nearest Neighbors) indexing. Registering the Model in OpenSearch We first register the model using OpenSearchs ML Commons API. This ensures compatibility when the model is deployed for inference. What's next? Thakur, eds.,

AWS 74

AWS K-nearest Neighbors Deep Learning Deep Learning 74