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10 Technical Blogs for Data Scientists to Advance AI/ML Skills

DataRobot Blog

With a goal to help data science teams learn about the application of AI and ML, DataRobot shares helpful, educational blogs based on work with the world’s most strategic companies. Explore these 10 popular blogs that help data scientists drive better data decisions. Taking a Multi-Tiered Approach to Model Risk Management.

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The synergy between UEM and medical device risk management

IBM Big Data Hub

Unified endpoint management (UEM) and medical device risk management concepts go side-by-side to create a robust cybersecurity posture that streamlines device management and ensures the safety and reliability of medical devices used by doctors and nurses at their everyday jobs.

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4 steps to improving your ESG risk management to increase financial performance

IBM Big Data Hub

Environmental, Social, and Governance (ESG) risk management has emerged as a critical aspect of business strategy for companies worldwide. Focusing on ESG Risk Management can help your organization become more profitable, and your organization can start on this journey today. Conduct ESG assessments.

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Can Machine Learning Address Risk Parity Concerns?

Smart Data Collective

Here at Smart Data Collective, we have blogged extensively about the changes brought on by AI technology. Over the past few months, many others have started talking about some of the changes that we blogged about for years. One of the most important changes pertains to risk parity management. What is risk parity?

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Gartner Explores Tech Innovations in Integrated Risk Management

John Wheeler

This week, we kicked-off a major research effort to explore current innovations in the rapidly expanding integrated risk management (IRM) market. This represents a great opportunity for organizations to utilize risk management technology (RiskTech) to bridge the gap between these seemingly disconnected transformation efforts.

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What is Model Risk and Why Does it Matter?

DataRobot Blog

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.