Applying ufuncs and reductions with explicit axis arguments, cumsum, cumprod, and diff. We use examples like normalizing a batch of vectors per feature or per sample. The goal is a reliable mental picture of N-dimensional reduction so you can align preprocessing with scikit-learn and with tensor axes in modern ML APIs.
