Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
You might notice that norms sound a lot like measures of distance. And if you remember Euclidean distances (think Pythagoras’ theorem) from grade school, then the concepts of non-negativity and the triangle inequality might ring a bell. In fact, the Euclidean distance is a norm: specifically it is the ℓ2 norm. Suppose that the elements in the 𝑛 -dimensional vector 𝐱 are 𝑥1,…,𝑥𝑛 . The :math:ell_2 norm of 𝐱 is the square root of the sum of the squares of the vector elements:
astonzhang
commented
4 years ago
ell_2is not displayed properly here.