https://github.com/himanshuteotia/maths_machine_learning
https://github.com/himanshuteotia/maths_machine_learning
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/himanshuteotia/maths_machine_learning
- Owner: himanshuteotia
- Created: 2020-01-08T09:04:59.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-01-08T09:48:55.000Z (over 5 years ago)
- Last Synced: 2024-12-27T08:27:52.200Z (5 months ago)
- Size: 1000 Bytes
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Maths for Machine Learning
## Linear Algebra
When formalizing (*give a definite structure or shape to*) intuitive concepts, a common approach is to construct a
set of objects (symbols) and a set of rules to manipulate these objects. This
is known as an algebra. Linear algebra is the study of vectors and certain
rules to manipulate vectors. The vectors many of us know from school are
called “geometric vectors”, which are usually denoted by a small arrow above the letter, e.g., →x and →y
In general, vectors are special objects that can be added together and
multiplied by scalars to produce another object of the same kind. From
an abstract mathematical viewpoint, any object that satisfies these two
properties can be considered a vector. Here are some examples of such
vector objects:
* Geometric vectors
* Polynomials
* Audio signals are vectors
* Elements of Rn (tuples of n real numbers) are vectors. Rn is more abstract than polynomials