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Automating Model Risk Compliance: Model Validation

DataRobot Blog

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52
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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Models can be designed, for instance, to discover relationships between various behavior factors.

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Synthetic data generation: Building trust by ensuring privacy and quality

IBM Big Data Hub

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 80
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How BIM Can Use AI to Increase Workflow Efficiency

Smart Data Collective

Ever since its emergence at the beginning of the century, building information modeling (BIM) has streamlined the construction process of buildings, up from their conception to execution. While artificially intelligent systems found their way into almost every household, the AEC industry is yet to reap the full extent of AI’s benefits.

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Ferrovial puts AI at the heart of its transformation

CIO Business Intelligence

There’s no defined hierarchical structure, but the Hub is based on a transversal and collaborative model where groups are created, and employees from all areas work on specific projects along with external experts. One of the main strategic transversal areas is AI. With this in mind, the AI ​​CoE acts along two clear lines at a global level.

IT 96
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12 most popular AI use cases in the enterprise today

CIO Business Intelligence

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

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Introducing the technology behind watsonx.ai, IBM’s AI and data platform for enterprise

IBM Big Data Hub

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. We stand on the frontier of an AI revolution.