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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning Blog

With ML-powered anomaly detection, customers can find outliers in their data without the need for manual analysis, custom development, or ML domain expertise. Using Amazon Glue Data Quality for anomaly detection Data engineers and analysts can use AWS Glue Data Quality to measure and monitor their data.

AWS 97
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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

General Purpose Tools These tools help manage the unstructured data pipeline to varying degrees, with some encompassing data collection, storage, processing, analysis, and visualization. DagsHub's Data Engine DagsHub's Data Engine is a centralized platform for teams to manage and use their datasets effectively.

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Training Models on Streaming Data [Practical Guide]

The MLOps Blog

Some industries rely not only on traditional data but also need data from sources such as security logs, IoT sensors, and web applications to provide the best customer experience. For example, before any video streaming services, users had to wait for videos or audio to get downloaded.

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Stream ingest data from Kafka to Amazon Bedrock Knowledge Bases using custom connectors

AWS Machine Learning Blog

Solution overview: Build a generative AI stock price analyzer with RAG For this post, we implement a RAG architecture with Amazon Bedrock Knowledge Bases using a custom connector and topics built with Amazon Managed Streaming for Apache Kafka (Amazon MSK) for a user who may be interested to understand stock price trends.