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? 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.

AWS 94

AWS Clustering Deep Learning Deep Learning 94

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

PyImageSearch

JANUARY 27, 2025

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

K-nearest Neighbors 102

K-nearest Neighbors Algorithm Data Preparation Database 102

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., The item ratings of these -closest neighbors are then used to recommend items to the given user. That’s not the case.

K-nearest Neighbors 57

K-nearest Neighbors Clustering Algorithm Deep Learning 57

ODSC - Open Data Science

JANUARY 5, 2024

It is a library for array manipulation that has been downloaded hundreds of times per month and stands at over 25,000 stars on GitHub. What makes it popular is that it is used in a wide variety of fields, including data science, machine learning, and computational physics. And did any of your favorites make it in?

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52