Rank and null space: reachable outputs and hidden input changes
Use rank, column space, and null space to understand a linear map. Explore rank-nullity, unreachable targets, and families of solutions with a small matrix experiment.
Writing
Clear accounts of what was tried and learned.
Explanations, tutorials, build notes, and essays grounded in work that can be examined. Explore a concept, try an experiment, and follow the reasoning behind it.
Start with the interactive foundationsShowing 97–101 of 101 posts
Tensors: read shapes, select values, and move axes
Learn tensors through a robot image batch. Explore shape, indexing, slicing, and axis order, then compare reshape with transpose using a runnable Python example.
Vector norms and normalization: L1, L2, and L∞
Measure vectors with L1, L2, and infinity norms. Explore unit boundaries, normalize a robot displacement, and distinguish zero vectors from tiny nonzero inputs.
Vector spaces: build direction from addition and scaling
Learn vector spaces through robot displacement. Explore span, linear independence, basis, and dimension with an interactive diagram, Python, and exercises.
Building a content pipeline that fails early
How this site validates MDX metadata, references, and publication state before a page is deployed.