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 127

SQL AWS Analytics Analytics 127

Flipboard

DECEMBER 18, 2024

It supports advanced features such as result highlighting, flexible pagination, and k-nearest neighbor (k-NN) search for vector and semantic search use cases.

K-nearest Neighbors 121

K-nearest Neighbors AWS ML ML 121

AWS Machine Learning Blog

NOVEMBER 15, 2024

For instance, analyzing large tables might require prompting the LLM to generate Python or SQL and running it, rather than passing the tabular data to the LLM. The embedded image is stored in an OpenSearch index with a k-nearest neighbors (k-NN) vector field. We give more details on that aspect later in this post.

Database 118

Database SQL Data Analysis Data Analysis 118

AWS Machine Learning Blog

FEBRUARY 13, 2025

This is the k-nearest neighbor (k-NN) algorithm. In k-NN, you can make assumptions around a data point based on its proximity to other data points. The SQL code for that is as follows: SELECT * FROM ( SELECT feed_articles.id This algorithm is used to perform classification and regression tasks.

AWS 108

AWS K-nearest Neighbors Clustering Algorithm 108

Towards AI

JULY 15, 2024

We shall look at various machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can install and call their libraries in R studios, including executing the code. In addition, it’s also adapted to many other programming languages, such as Python or SQL.

Machine Learning 119

Machine Learning Machine Learning Algorithm K-nearest Neighbors 119

Pickl AI

SEPTEMBER 12, 2024

K K-Means Clustering: An unsupervised learning algorithm that partitions data into K distinct clusters based on feature similarity. K-Nearest Neighbors (KNN): A simple, non-parametric classification algorithm that assigns a class to a data point based on the majority class of its K nearest neighbours.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance. This trade-off can easily be reversed by increasing the k value which in turn results in increasing the number of neighbours. Is Python and SQL enough for data science? Let us see some examples.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52