Which mathematician's work on Bayesian probability theory became fundamental to machine learning algorithms now used in adaptive mathematics learning platforms?

Machine learning has revolutionized mathematics education products and analytical tools. Behind the algorithms powering these educational innovations are key mathematical concepts and pioneering researchers. This poll tests your knowledge of the foundational mathematical work that enables today's AI-powered math learning platforms, adaptive tutoring systems, and automated problem-solving tools that are transforming mathematics education and practice.

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Thomas Bayes (1701-1761), whose theorem forms the foundation for probabilistic machine learning approaches in educational software
Leonhard Euler (1707-1783), whose work on graph theory directly led to the development of neural networks
Carl Friedrich Gauss (1777-1855), who developed the first statistical learning algorithm specifically for mathematics education
Ada Lovelace (1815-1852), who created the initial mathematical framework for machine learning in her notes on the Analytical Engine