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 122

K-nearest Neighbors AWS Machine Learning Machine Learning 122

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 125

AWS ML ML Database 125

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. For more information about the natural language understanding-powered search functionalities of OpenSearch Service, refer to Building an NLU-powered search application with Amazon SageMaker and the Amazon OpenSearch Service KNN feature.

AWS 97

AWS ML ML Machine Learning 97

Mlearning.ai

JUNE 6, 2023

How to perform Face Recognition using KNN In this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. Natural Language Processing Projects with source code in Python 69. Its accuracy is slightly less compared to these big boys like MTCNNs.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52