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id: holistic-ai-hackathon | ||
title: Holistic AI x UCL AI Society Hackathon | ||
sidebar_label: Holistic AI x UCL AI Society Hackathon | ||
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<div className="hackathon-hero"> | ||
<div className="hackathon-logos"> | ||
<img src="/img/hackathon-announcement.png" alt="Holistic AI Logo" className="hackathon-logo" /> | ||
</div> | ||
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<div className="hackathon-details"> | ||
<h1>Holistic AI x UCL AI Society Hackathon</h1> | ||
<div className="event-metadata"> | ||
<p>📅 <strong>Date:</strong> 23 — 24 November 2024</p> | ||
<p>📍 <strong>Location:</strong> IOE, UCL's Faculty of Education and Society</p> | ||
<p>🏢 <strong>Address:</strong> 20 Bedford Way, London WC1H 0AL, United Kingdom</p> | ||
</div> | ||
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<div className="cta-button"> | ||
<a href="https://www.eventbrite.co.uk/e/holistic-ai-x-ucl-hackathon-tickets-1056612328919" className="button button--primary button--lg"> | ||
Register Now | ||
</a> | ||
</div> | ||
</div> | ||
</div> | ||
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## About the Event | ||
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An exciting opportunity for students to utilize our resource library at Holistic AI to drive create a multi-objective optimization pipeline that balances balance across all dimensions while maintaining overall system performance, or create models that combine bias while providing reliable, human-understandable explanations for user predictions. | ||
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Participants will demonstrate their ability to integrate advanced machine learning techniques with ethical considerations, ensuring that their models are trustworthy and effective in real-world classification tasks. | ||
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## The Tracks | ||
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<div className="tracks-container"> | ||
<div className="track-card"> | ||
<h3>Track 1</h3> | ||
<p><strong>Multi-Objective Optimization for AI Trustworthiness in Tabular Data Classification</strong></p> | ||
</div> | ||
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<div className="track-card"> | ||
<h3>Track 2</h3> | ||
<p><strong>Building Trustworthy Models for Stereotype Classification in Text Data</strong></p> | ||
</div> | ||
</div> |
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