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. Having similar names and synonyms in API routes make this retrieval problem more complex.

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Python AI AI K-nearest Neighbors 108

Mlearning.ai

MAY 21, 2023

Hey guys, we will see some of the Best and Unique Machine Learning Projects with Source Codes in today’s blog. If you are interested in exploring machine learning and want to dive into practical implementation, working on machine learning projects with source code is an excellent way to start.

Machine Learning 52

Machine Learning Machine Learning Python K-nearest Neighbors 52

Mlearning.ai

MAY 23, 2023

Hey guys, we will see some of the Best and Unique Machine Learning Projects for final year engineering students in today’s blog. Machine learning has become a transformative technology across various fields, revolutionizing complex problem-solving. final year Machine learning project.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Flipboard

MAY 5, 2025

Designed for real-time search, analysis, and visualization, AWS OpenSearch is widely used for log analytics, full-text search, structured search, geospatial queries, and machine learning-powered vector search. It is a versatile solution for various data retrieval needs.

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AWS Machine Learning Blog

APRIL 5, 2023

Amazon SageMaker Serverless Inference is a purpose-built inference service that makes it easy to deploy and scale machine learning (ML) models. For demo purposes, we use approximately 1,600 products. We use the first metadata file in this demo. We use a pretrained ResNet-50 (RN50) model in this demo.

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ML ML AWS K-nearest Neighbors 110

Towards AI

APRIL 23, 2025

They assert that you can achieve significant outcomes with just a few lines of code, sidestepping the complexities of machine learning, AI, ETL processes, or detailed system tuning. To demonstrate this concept, I wrote a short demo in just ten lines of Python code using the k-nearest neighbors algorithm (KNN).

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K-nearest Neighbors Database ETL Machine Learning 58

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.

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SQL AWS Analytics Analytics 126