ODSC - Open Data Science

DECEMBER 14, 2023

Photo Mosaics with Nearest Neighbors: Machine Learning for Digital Art In this post, we focus on a color-matching strategy that is of particular interest to a data science or machine learning audience because it utilizes a K-nearest neighbors (KNN) modeling approach.

K-nearest Neighbors 97

K-nearest Neighbors AI AI Machine Learning 97

AWS Machine Learning Blog

FEBRUARY 5, 2025

The following diagram illustrates the data pipeline for indexing and query in the foundational search architecture. The neural search pipeline forwards each search request to the same Amazon Titan Multimodal Embeddings model to convert the text and images into multi-dimensional vector embeddings.

K-nearest Neighbors 89

K-nearest Neighbors Machine Learning Machine Learning Database 89

AWS Machine Learning Blog

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

SQL 133

SQL AWS Analytics Analytics 133

DagsHub

DECEMBER 23, 2024

They are: Based on shallow, simple, and interpretable machine learning models like support vector machines (SVMs), decision trees, or k-nearest neighbors (kNN).   Traditional Active Learning has the following characteristics. Relies on explicit decision boundaries or feature representations for sample selection.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52