AWS Machine Learning Blog

APRIL 5, 2023

For demo purposes, we use approximately 1,600 products. We use the first metadata file in this demo. We use a pretrained ResNet-50 (RN50) model in this demo. This includes configuring an OpenSearch Service cluster, ingesting item embedding, and performing free text and image search queries. bin/bash MODEL_NAME=RN50.pt

ML 110

ML ML AWS K-nearest Neighbors 110

Mlearning.ai

MAY 23, 2023

How to perform Face Recognition using KNN So in this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. Check out the demo here… [link] 21. Check out the demo here… [link] 24. Check out the demo here… [link] 25. This is a simple project.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Mlearning.ai

MAY 21, 2023

How to perform Face Recognition using KNN So in this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. Check out the demo here… [link] 21. Check out the demo here… [link] 24. Check out the demo here… [link] 25. This is a simple project.

Machine Learning 52

Machine Learning Machine Learning Python K-nearest Neighbors 52

Snorkel AI

JANUARY 26, 2023

We tackle that by learning these clusters in the foundation models embedding space and providing those clusters as the subgroups—and basically learning a weak supervision model on each of those clusters. So, we propose to do this sort of K-nearest-neighbors-type extension per source in the embedding space.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

Snorkel AI

JANUARY 26, 2023

We tackle that by learning these clusters in the foundation models embedding space and providing those clusters as the subgroups—and basically learning a weak supervision model on each of those clusters. So, we propose to do this sort of K-nearest-neighbors-type extension per source in the embedding space.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

AWS Machine Learning Blog

NOVEMBER 1, 2024

We tried different methods, including k-nearest neighbor (k-NN) search of vector embeddings, BM25 with synonyms , and a hybrid of both across fields including API routes, descriptions, and hypothetical questions. The request arrives at the microservice on our existing Amazon Elastic Container Service (Amazon ECS) cluster.

Python 108

Python AI AI K-nearest Neighbors 108