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

AWS Machine Learning Blog

NOVEMBER 13, 2024

To upload the dataset Download the dataset : Go to the Shoe Dataset page on Kaggle.com and download the dataset file (350.79MB) that contains the images. To search against the database, you can use a vector search, which is performed using the k-nearest neighbors (k-NN) algorithm.

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AWS Database K-nearest Neighbors AI 120

Flipboard

MAY 5, 2025

Jump Right To The Downloads Section Introduction What Is AWS OpenSearch? Amazon OpenSearch Service is a fully managed solution that simplifies the deployment, operation, and scaling of OpenSearch clusters in the AWS Cloud. For this setup: Choose 1 data node and let it handle both data processing and cluster management.

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AWS Clustering Deep Learning Deep Learning 118

PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Spectral clustering, a technique rooted in graph theory, offers a unique way to detect anomalies by transforming data into a graph and analyzing its spectral properties.

Clustering 57

Clustering Algorithm Machine Learning Machine Learning 57

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

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AWS K-nearest Neighbors Deep Learning Deep Learning 74

PyImageSearch

JUNE 19, 2023

K-Nearest Neighbor K-nearest neighbor (KNN) ( Figure 8 ) is an algorithm that can be used to find the closest points for a data point based on a distance measure (e.g., Figure 8: K-nearest neighbor algorithm (source: Towards Data Science ). Several clustering algorithms (e.g.,

K-nearest Neighbors 57

K-nearest Neighbors Clustering Algorithm Deep Learning 57

AWS Machine Learning Blog

APRIL 19, 2024

This solution includes the following components: Amazon Titan Text Embeddings is a text embeddings model that converts natural language text, including single words, phrases, or even large documents, into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity.

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