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linear-algebra

Matrices: notation, shape, and special forms

taught

Taught in

Images as tensors: shape, channels, and batches
Computer Vision
A matrix is a table, one row per neuron
Deep Learning / Neural Networks
Shapes and the batch dimension
Deep Learning / Neural Networks
Shape
Deep Learning / Neural Networks
Scalars, vectors, matrices, and tensors, revisited for images
Digital Image Processing
Matrices — notation, shape, and special forms
Linear Algebra — Vectors, Matrices, and the Geometry of Data

Requires

partial-pivoting-and-why-a-computer-eliminates required

Required by

Image tensors -- batch and channel conventions for vision models required
Matrix addition and scalar multiplication required
Reading an array's .shape required
The batch dimension and broadcasting, as engineering convention required

Local knowledge map

Local knowledge map

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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.