The MLOps Blog

MAY 17, 2023

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

ETL 59

ETL ML Machine Learning Data Scientist 59

Snorkel AI

JULY 5, 2023

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?

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

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?

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

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?

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Flipboard

NOVEMBER 27, 2024

Customers want to search through all of the data and applications across their organization, and they want to see the provenance information for all of the documents retrieved. 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.

Metadata 148

Metadata Auto-complete Data Discovery ML Engineer 148