AWS Machine Learning Blog
OCTOBER 16, 2024
With a growing library of long-form video content, DPG Media recognizes the importance of efficiently managing and enhancing video metadata such as actor information, genre, summary of episodes, the mood of the video, and more. Video data analysis with AI wasn’t required for generating detailed, accurate, and high-quality metadata.
Marktechpost
NOVEMBER 19, 2024
Introduction to LAION-DISCO-12M To address this gap, LAION AI has released LAION-DISCO-12M—a collection of 12 million links to publicly available YouTube samples, paired with metadata designed to support foundational machine learning research in audio and music. Don’t Forget to join our 55k+ ML SubReddit.
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NOVEMBER 22, 2024
This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. The data mesh architecture aims to increase the return on investments in data teams, processes, and technology, ultimately driving business value through innovative analytics and ML projects across the enterprise.
FEBRUARY 11, 2025
By using Amazon Q Business, which simplifies the complexity of developing and managing ML infrastructure and models, the team rapidly deployed their chat solution. For the metadata file used in this example, we focus on boosting two key metadata attributes: _document_title and services.
OCTOBER 25, 2023
However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data. But in the case of unstructured data, metadata discovery is challenging because the raw data isn’t easily readable.
APRIL 10, 2025
You can get started without any prior machine learning (ML) experience, and Amazon Personalize allows you to use APIs to build sophisticated personalization capabilities. For this example, we use the ml-latest-small dataset from the MovieLens dataset to simulate user-item interactions.
AWS Machine Learning Blog
JULY 2, 2024
With metadata filtering now available in Knowledge Bases for Amazon Bedrock, you can define and use metadata fields to filter the source data used for retrieving relevant context during RAG. Metadata filtering gives you more control over the RAG process for better results tailored to your specific use case needs.
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