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What is Model Risk and Why Does it Matter?

DataRobot Blog

In 2011, the Federal Reserve Board (FRB) and the Office of Comptroller of the Currency (OCC) issued a joint regulation specifically targeting Model Risk Management (respectively, SR 11-7 and OCC Bulletin 2011-12 ). The regulators have provided a universal definition that has been adopted across the financial industry.

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Build verifiable explainability into financial services workflows with Automated Reasoning checks for Amazon Bedrock Guardrails

AWS Machine Learning Blog

Rather than using probabilistic approaches such as traditional machine learning (ML), Automated Reasoning tools rely on mathematical logic to definitively verify compliance with policies and provide certainty (under given assumptions) about what a system will or wont do. However, its important to understand its limitations.

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Automating Model Risk Compliance: Model Development

DataRobot Blog

It has been over a decade since the Federal Reserve Board (FRB) and the Office of the Comptroller of the Currency (OCC) published its seminal guidance focused on Model Risk Management ( SR 11-7 & OCC Bulletin 2011-12 , respectively). With this definition of model risk, how do we ensure the models we build are technically correct?

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Data Catalogs: A Category of Their Own

Alation

According to the report, MLDCs are becoming increasingly valuable for organizations implementing self-service analytics: Combining ML with collaboration and activation scales out data understanding and speeds up use. 7] Harvard Business Review, Category Creation Is the Ultimate Growth Strategy, Eddie Yoon, September 26, 2011.

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Top 10 Deep Learning Platforms in 2024

DagsHub

This guarantees businesses can fully utilize deep learning in their AI and ML initiatives. You can make more informed judgments about your AI and ML initiatives if you know these platforms' features, applications, and use cases. In 2011, H2O.ai Further Reading and Documentation H2O.ai Documentation H2O.ai

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Optimized Deep Learning Pipelines: A Deep Dive into TFRecords and Protobufs (Part 2)

Heartbeat

Tensorflow’s Feature proto definition. Tensorflow’s “Features” proto definition Because our raw data is contained as either BytesList, FloatList, or Int64List and wrapped in a “oneof” Feature proto, that simplifies the map (and thus justifies the design choice). To do this, we first create a “Feature” proto.