Section 1 of 12 · 3 lessons

Introductory Mathematics

Machine learning uses mathematics to describe data, make predictions, and improve those predictions. Those calculations are much easier to follow when we understand what they are doing. We will work through statistics, linear algebra, and calculus from small examples, so you don't need to arrive with that background.

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  1. 01Statistics & Probability PrimerA collection of measurements does not explain itself. We need ways to describe what is typical, how much the values differ, and how much confidence we should place in the patterns we observe.
  2. 02Linear Algebra PrimerA model often needs to work with many measurements at once. Vectors and matrices let us organise those numbers and repeat useful calculations without writing a separate rule for every example.
  3. 03Calculus PrimerIf we change a model's setting a little, does its error improve or get worse? Calculus gives us a way to describe that change and use it to decide what to adjust next.