Math intimidation? Marianne Hoornenborg shows that the core of AI is built on surprisingly simple concepts. In her beginner-friendly talk, she breaks down how boolean logic fuels decision trees, floating-point precision shapes confidence scores, and vector geometry drives recommendation engines.
You’ll even revisit the basics of binary and hexadecimal at the machine level—all through hands-on Java examples that make these ideas click. Whether you’re brand new or just brushing off old knowledge, this session proves AI math is way more approachable than you’d expect.
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