AWS Machine Learning Blog

DECEMBER 10, 2024

Part 1 uses AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless. We performed a k-nearest neighbor (k-NN) search to retrieve the most relevant embedding matching the question. You can do this by deleting the stacks using the AWS CloudFormation console.

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AWS Machine Learning Blog

JUNE 3, 2024

Kinesis Video Streams makes it straightforward to securely stream video from connected devices to AWS for analytics, machine learning (ML), playback, and other processing. This solution was created with AWS Amplify. It enables real-time video ingestion, storage, encoding, and streaming across devices.

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AWS Machine Learning Blog

JANUARY 30, 2024

and AWS services including Amazon Bedrock and Amazon SageMaker to perform similar generative tasks on multimodal data. In this post, we use the slide deck titled Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023, to demonstrate the solution.

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AWS Machine Learning Blog

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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AWS Machine Learning Blog

JANUARY 6, 2023

Many AWS media and entertainment customers license IMDb data through AWS Data Exchange to improve content discovery and increase customer engagement and retention. We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. Background. Solution overview. Launch solution resources.

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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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Flipboard

FEBRUARY 7, 2025

You will execute scripts to create an AWS Identity and Access Management (IAM) role for invoking SageMaker, and a role for your user to create a connector to SageMaker. An AWS account You will need to be able to create an OpenSearch Service domain and two SageMaker endpoints. Python The code has been tested with Python version 3.13.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

For instance, it can reveal the preferences of play callers, allow deeper understanding of how respective coaches and teams continuously adjust their strategies based on their opponent’s strengths, and enable the development of new defensive-oriented analytics such as uniqueness of coverages ( Seth et al. ). She received her Ph.D.

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Pickl AI

NOVEMBER 18, 2024

Predictive analytics uses historical data to forecast future trends, such as stock market movements or customer churn. K-Nearest Neighbors), while others can handle large datasets efficiently (e.g., Common Applications of Machine Learning Machine Learning has numerous applications across industries. Random Forests).

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Flipboard

MAY 30, 2025

To help you replicate this setup, weve provided the necessary source code, an Amazon SageMaker notebook, and an AWS CloudFormation template. Add the IAM role mentioned previously to map it to the ml_full_access role, this will allow OpenSearch to access the needed AWS resources from the ml-commons plugin.

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