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. Or has to involve complex mathematics and equations? Thats not the case.

AWS 82

AWS Clustering Deep Learning Deep Learning 82

PyImageSearch

MAY 12, 2025

Powering Neural Search : Enables advanced similarity-based retrieval using OpenSearchs k-NN (k-Nearest Neighbors) indexing. By defining an index mapping correctly, OpenSearch can efficiently store and retrieve movie data while leveraging k-NN (k-Nearest Neighbors) search to find similar movies based on embeddings.

AWS 74

AWS K-nearest Neighbors Deep Learning Deep Learning 74

PyImageSearch

JANUARY 27, 2025

On Line 28 , we sort the distances and select the top k nearest neighbors. Download the Source Code and FREE 17-page Resource Guide Enter your email address below to get a.zip of the code and a FREE 17-page Resource Guide on Computer Vision, OpenCV, and Deep Learning. Huot, and P. Thakur, eds., Download the code!

K-nearest Neighbors 102

K-nearest Neighbors Algorithm Data Preparation Database 102