Remove Interactive Remove Knowledge Discovery Remove Measurement Remove Optimization
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Understanding Social And Collaborative Business Intelligence

datapine

This is done using interactive Business Intelligence and Analytics dashboards along with intuitive tools to improve data clarity. Resources can be optimized through this type of sharing by allowing users to access reports, dashboards, and data that can possibly be just what they require to complete a task or analysis.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

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Understanding Social And Collaborative Business Intelligence

datapine

This is done using interactive Business Intelligence and Analytics dashboards along with intuitive tools to improve data clarity. Resources can be optimized through this type of sharing by allowing users to access reports, dashboards, and data that can possibly be just what they require to complete a task or analysis.

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Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies

Ontotext

This dramatically simplifies the interaction with complex databases and analytics systems. Join us as we demystify the methodologies empowering such implementations, shed light on their range of capabilities, and detail how Ontotext is harnessing these technologies to bring transformative enhancements to our data interaction landscape.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature.

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