The maths you actually need, and what you can skip

Enough intuition to read ML material. Explicitly not a maths degree.

1. Vectors, and what they actually represent Read a vector as a point, a direction, and a list of features.
2. The dot product, and why similarity is just an angle Explain why two similar things have a large dot product.
3. Matrices as transformations See a matrix as something that moves space, not a grid of numbers.
4. Mean, variance and distributions Describe a dataset's centre and spread, and read a histogram.
5. Probability, intuitively Reason about likelihood and conditional probability without formulas.
6. What a derivative actually is Read a derivative as a slope, which is all gradient descent needs.

Ends with a graded checkpoint: 8 questions, pass mark 65%.