The MLOps Blog

MAY 17, 2023

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. What is an ETL data pipeline in ML? Let’s look at the importance of ETL pipelines in detail.

ETL 59

ETL ML Machine Learning Data Scientist 59

Snorkel AI

JUNE 30, 2023

You have to make sure that your ETLs are locked down. And usually what ends up happening is that some poor data scientist or ML engineer has to manually troubleshoot this in a Jupyter Notebook. So this path on the right side of the production icon is what we’re calling ML observability.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

Snorkel AI

JUNE 30, 2023

You have to make sure that your ETLs are locked down. And usually what ends up happening is that some poor data scientist or ML engineer has to manually troubleshoot this in a Jupyter Notebook. So this path on the right side of the production icon is what we’re calling ML observability.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

Generative AI 103

Generative AI Prompt Engineer Prompt Engineering AI 103