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

Marktechpost

In the actual world, machine learning (ML) systems can embed issues like societal prejudices and safety worries. Understanding patterns of model output for subgroups or slices of input data goes beyond examining aggregate metrics like accuracy or F1 score. Zeno works together with other systems and combines the methods of others.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

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.

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

Snorkel AI

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Is more data always better? AR : Absolutely.

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

Snorkel AI

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Is more data always better? AR : Absolutely.