PyImageSearch

DECEMBER 23, 2024

This lesson is the 1st in a 2-part series on Mastering Approximate Nearest Neighbor Search : Implementing Approximate Nearest Neighbor Search with KD-Trees (this tutorial) Approximate Nearest Neighbor with Locality Sensitive Hashing (LSH) To learn how to implement an approximate nearest neighbor search using KD-Tree , just keep reading.

K-nearest Neighbors 118

K-nearest Neighbors Algorithm Deep Learning Deep Learning 118

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?

K-nearest Neighbors 91

K-nearest Neighbors AWS Deep Learning Deep Learning 91

Flipboard

MAY 5, 2025

Jump Right To The Downloads Section Introduction What Is AWS OpenSearch? Business Intelligence and Data Visualization: Uses OpenSearch Dashboards to explore, analyze, and visualize structured and unstructured data in real time. My mission is to change education and how complex Artificial Intelligence topics are taught.

AWS 119

AWS Clustering Deep Learning Deep Learning 119

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 139

K-nearest Neighbors AWS Machine Learning Machine Learning 139

PyImageSearch

MAY 12, 2025

Jump Right To The Downloads Section Introduction In the previous blog , we covered the end-to-end setup of AWS OpenSearch, from deploying an OpenSearch domain to indexing and retrieving test data, as well as testing access via API and OpenSearch Dashboards to ensure everything was functioning correctly. data queries_set_1.txt

AWS 74

AWS K-nearest Neighbors Deep Learning Deep Learning 74

AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this analysis, we use a K-nearest neighbors (KNN) model to conduct crop segmentation, and we compare these results with ground truth imagery on an agricultural region. This example uses the Python client to identify and download imagery needed for the analysis.

Machine Learning 138

Machine Learning Machine Learning ML ML 138

AWS Machine Learning Blog

APRIL 19, 2024

We perform a k-nearest neighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. This notebook will download a publicly available slide deck , convert each slide into the JPG file format, and upload these to the S3 bucket. We run these notebooks one by one. I need numbers."

AWS 131

AWS ML ML Database 131