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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. There are at least four major ways for data scientists to find bugs in ML models: sensitivity analysis, residual analysis, benchmark models, and ML security audits. Sensitivity analysis.

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Managing risk in machine learning

O'Reilly on Data

At the recent Strata Data conference we had a series of talks on relevant cultural, organizational, and engineering topics. Here's a list of a few clusters of relevant sessions from the recent conference: Data Integration and Data Pipelines. Data Platforms. Model lifecycle management.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

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Back to the Financial Regulatory Future

Cloudera

From stringent data protection measures to complex risk management protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes. This results in enhanced efficiency in compliance processes.

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AI Technology is Invaluable for Cybersecurity

Smart Data Collective

As a result, businesses across many industries have been spending increasingly large sums on security technology and services, driving demand for trained specialists fluent in the latest preventative measures. After evaluating potential risks, cybersecurity professionals implement various preventative actions.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

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Five areas where EA matters more than ever

CIO Business Intelligence

That requires enterprise architects to work more closely with risk management and security staff to understand dependencies among the components in the architecture to better understand the likelihood and severity of disruptions and formulate plans to cope with them.