In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...
This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...
From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with projects that support AI development.
Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...
Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights – including a model-estimated probability score ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
The greatest risk in financial AI isn't that machines will make mistakes. It's that institutions will believe they understand those machines when they don't.
In an era where AI adoption frequently outpaces regulatory readiness, Archana Pattabhi, Senior Vice President at a leading global bank, led a forward-looking transformation that redefined how ...
Overview: AI is transforming medical diagnosis by allowing earlier and more accurate disease detection.Machine learning ...
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