PyImageSearch

DECEMBER 23, 2024

Or think about a real-time facial recognition system that must match a face in a crowd to a database of thousands. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. Imagine a database with billions of samples ( ) (e.g., Imagine a database with billions of samples ( ) (e.g.,

K-nearest Neighbors 118

K-nearest Neighbors Algorithm Deep Learning Deep Learning 118

AWS Machine Learning Blog

NOVEMBER 13, 2024

It works by analyzing the visual content to find similar images in its database. Store embeddings : Ingest the generated embeddings into an OpenSearch Serverless vector index, which serves as the vector database for the solution. Display results : Display the top K similar results to the user. b64encode(resized_image).decode('utf-8')

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PyImageSearch

MAY 19, 2025

Jump Right To The Downloads Section Introduction In the previous post , we walked through the process of indexing and storing movie data in OpenSearch. In this tutorial, well explore how OpenSearch performs k-NN (k-Nearest Neighbor) search on embeddings. Looking for the source code to this post?

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K-nearest Neighbors AWS Deep Learning Deep Learning 91

Flipboard

FEBRUARY 7, 2025

This post shows you how to set up RAG using DeepSeek-R1 on Amazon SageMaker with an OpenSearch Service vector database as the knowledge base. When combined with Amazon OpenSearch Service , it enables robust Retrieval Augmented Generation (RAG) applications.

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Database AWS Python ML 86

AWS Machine Learning Blog

APRIL 3, 2024

We detail the steps to use an Amazon Titan Multimodal Embeddings model to encode images and text into embeddings, ingest embeddings into an OpenSearch Service index, and query the index using the OpenSearch Service k-nearest neighbors (k-NN) functionality. You then display the top similar results.

K-nearest Neighbors 138

K-nearest Neighbors AWS Machine Learning Machine Learning 138

Flipboard

MAY 5, 2025

In this series, we will set up AWS OpenSearch , which will serve as a vector database for a semantic search application that well develop step by step. Jump Right To The Downloads Section Introduction What Is AWS OpenSearch? 1 Creating a Sample Index An index in OpenSearch is like a database table where data is stored.

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AWS Machine Learning Blog

APRIL 19, 2024

We stored the embeddings in a vector database and then used the Large Language-and-Vision Assistant (LLaVA 1.5-7b) 7b) model to generate text responses to user questions based on the most similar slide retrieved from the vector database. OpenSearch Serverless is an on-demand serverless configuration for Amazon OpenSearch Service.

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