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Explore the intersection of machine learning and pure mathematics in this 58-minute conference talk delivered at Harvard CMSA's Big Data Conference 2025. Discover how machine learning techniques can contribute to mathematical research and problem-solving as Jordan Ellenberg from UW Madison examines the potential applications, benefits, and implications of incorporating computational learning methods into mathematical practice. Learn about emerging opportunities where artificial intelligence and machine learning algorithms can assist mathematicians in discovering patterns, generating conjectures, and advancing theoretical understanding across various mathematical domains.
