Flipboard

NOVEMBER 17, 2023

Set up a MongoDB cluster To create a free tier MongoDB Atlas cluster, follow the instructions in Create a Cluster. MongoDB Atlas Vector Search uses a technique called k-nearest neighbors (k-NN) to search for similar vectors. k-NN works by finding the k most similar vectors to a given vector.

K-nearest Neighbors 170

K-nearest Neighbors AWS Clustering Database 170

Towards AI

APRIL 14, 2023

The prediction is then done using a k-nearest neighbor method within the embedding space. The feature space reduction is performed by aggregating clusters of features of balanced size. This clustering is usually performed using hierarchical clustering.

K-nearest Neighbors 98

K-nearest Neighbors Algorithm Clustering Support Vector Machines 98

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., Figure 8: K-nearest neighbor algorithm (source: Towards Data Science ). Several clustering algorithms (e.g.,

K-nearest Neighbors 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

Snorkel AI

APRIL 11, 2023

Now the key insight that we had in solving this is that we noticed that unseen concepts are actually well clustered by pre-trained deep learning models or foundation models. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components. of the unlabeled data.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Now the key insight that we had in solving this is that we noticed that unseen concepts are actually well clustered by pre-trained deep learning models or foundation models. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components. of the unlabeled data.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Now the key insight that we had in solving this is that we noticed that unseen concepts are actually well clustered by pre-trained deep learning models or foundation models. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components. of the unlabeled data.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 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 118

Python AI AI K-nearest Neighbors 118