January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Matrix properties
In this section, we will look at some of the important properties matrices which are very useful for deep learning applications.
- Norm: Norm is an important property of a vector or a matrix that measures the size of the vector or the matrix. Geometrically it can also be interpreted as the distance of a point, x, from an origin. A Lp norm is therefore defined as follows:
Though a norm can be computed for various orders of p, most popularly known norms are L1 and L2 norm. L1 norm is usually considered a good choice for sparse models:
Another norm popular in the deep learning community is the max norm, also referred to as ...
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