Flipboard

MAY 5, 2025

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. Or has to involve complex mathematics and equations? Thats not the case.

AWS 95

AWS Clustering Deep Learning Deep Learning 95

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. bin/bash MODEL_NAME=RN50.pt

ML 118

ML ML AWS K-nearest Neighbors 118

Mlearning.ai

MAY 23, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Mlearning.ai

MAY 21, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

Machine Learning 52

Machine Learning Machine Learning Python K-nearest Neighbors 52