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 101

K-nearest Neighbors Algorithm Deep Learning Deep Learning 101

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 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

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 82

K-nearest Neighbors Algorithm Data Preparation Database 82

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

AWS Machine Learning Blog

JANUARY 6, 2023

We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. In this post, we present a solution to handle OOC situations through knowledge graph-based embedding search using the k-nearest neighbor (kNN) search capabilities of OpenSearch Service. Solution overview.

AWS 100

AWS ML ML Machine Learning 100

PyImageSearch

SEPTEMBER 16, 2024

Jump Right To The Downloads Section Understanding Anomaly Detection: Concepts, Types, and Algorithms What Is Anomaly Detection? For instance, if a user who typically accesses the network during business hours suddenly logs in at midnight and starts downloading large amounts of data, this behavior would be considered anomalous.

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

AWS Machine Learning Blog

APRIL 5, 2023

k-NN index query – This is the inference phase of the application. In this phase, you submit a text search query or image search query through the deep learning model (CLIP) to encode as embeddings. Then, you use those embeddings to query the reference k-NN index stored in OpenSearch Service.

ML 109

ML ML AWS K-nearest Neighbors 109