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What are Joint, Marginal, and Conditional Probability?

Analytics Vidhya

Probability is a cornerstone of statistics and data science, providing a framework to quantify uncertainty and make predictions. Probability measures the likelihood of an event […] The post What are Joint, Marginal, and Conditional Probability? This article unpacks these concepts with clear explanations and examples.

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Measuring Models' Uncertainty: Conformal Prediction

Dataiku

For designing machine learning (ML) models as well as for monitoring them in production, uncertainty estimation on predictions is a critical asset. It helps identify suspicious samples during model training in addition to detecting out-of-distribution samples at inference time.

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South Korea’s political unrest threatens the stability of global tech supply chains

CIO Business Intelligence

The reversal calmed immediate fears of an extended crisis, but the political instability sent ripples through financial markets and heightened uncertainty for South Korea’s role as a global technology hub. The stalemate is far from over, with uncertainty prevailing amid growing calls for the president’s impeachment.

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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

How will you measure success? So now we have a user persona, several scenarios, and a way to measure success. Business value : Align outputs with business metrics and optimize workflows to achieve measurable ROI. LLM-powered software amplifies this uncertainty further. Vibes are a fine starting pointjust dont stop there.

Testing 168
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Sustainability: Real progress but also thorny challenges ahead

CIO Business Intelligence

Dealing with uncertain economic environments, which can distract from sustainability issues: Energy prices, price inflation, and geopolitical tensions continue to fluctuate, and that uncertainty can impact focus on environmental sustainability. So far, however, companies seem to be staying the course.

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You Can’t Regulate What You Don’t Understand

O'Reilly on Data

If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. But alignment will be impossible without robust institutions for disclosure and auditing. That is a crucial first step, and we should take it immediately.

Metrics 359
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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”