Raising to the T in machine learning

What does it mean when in a machine learning paper there is $$(arg)^{T}$$, what does the T does to an arg in this 3b1b video on neural networks he puts the: $$(w^{l-1})^{T}$$

• In what context is this? could you provide the paper so we can see it ourselves? Or even better - quote it. Anyhow, raising to $T$ could be the transpose matrix when in context of linear algebra maths, but it also could just be a regular number and raising some other number to its power. Or, it could be something the authors of the paper defined themselves – nir shahar Apr 3 at 22:44
• Yeah most likely transpose of a vector or matrix. – awillia91 Apr 4 at 0:17
• Please edit your question to provide more context. – D.W. Apr 4 at 1:42

The notation $$A^T$$ stands for the transpose of a matrix. It is not specific to machine learning, but rather standard notation in linear algebra. Other notations are sometimes used, for example $$A'$$.
A related operation is the adjoint $$A^*$$. The transpose and adjoint are equal for real matrices.