Remove Data Discovery Remove Metadata Remove ML Engineer
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Search enterprise data assets using LLMs backed by knowledge graphs

Flipboard

The application needs to search through the catalog and show the metadata information related to all of the data assets that are relevant to the search context. Solution overview The solution integrates with your existing data catalogs and repositories, creating a unified, scalable semantic layer across the entire data landscape.

Metadata 149
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CMU Researchers Introduce Zeno: A Framework for Behavioral Evaluation of Machine Learning (ML) Models

Marktechpost

Understanding patterns of model output for subgroups or slices of input data goes beyond examining aggregate metrics like accuracy or F1 score. Stakeholders such as ML engineers, designers, and domain experts must work together to identify a model’s expected and potential faults.

professionals

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. So does that mean feature selection is no longer necessary? Robert, you can go first.

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. So does that mean feature selection is no longer necessary? Robert, you can go first.

article thumbnail

Google experts on practical paths to data-centricity in applied AI

Snorkel AI

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. So does that mean feature selection is no longer necessary? Robert, you can go first.