# Linear algebra is part of mathematics.

The simple numerical exercises that begin each exercise is  only help you check your understanding of basic procedures is the concept of linear algebra it is also important as the computations.

Linear algebra is a language,material presented in one section is not easily understood to unless you have truly studies the more and the walk the exercise for the each section, it is also a framework for understanding how  the the combinations may proceed.
Linear algebra is imported to describe any complex equations because of the higher demand for increased computing powers for computer science and mathematician work in a numerical linear algebra to develop faster and more reliable algorithms for computations and electrical engineers design faster and smaller computers to run the algorithms it is also used in machine learnings and artificial intelligence.

# Linear algebra is seen many different ways.

Applications
Abstraction
Computation
Visualisation

## There are many ways to understand linear algebra

Modern view of matrix multiplication, good notations is crucial, and the text reflects the way scientist and engineers actually use linear algebra in practice. Main theme is to view a matrix vector product Ax as a linear combination of the column of A.
Orthogonality and least square problems
These topics receive a more comprehensive treatment then each commonly found in beginning text.it has emphasized the need for a substantial you need on orthogonality and least square problem because orthogonality plays an important role in computer calculations and numerical linear algebra and because inconsistent linear systems arrives to orphan in a practical work.
Eigenvalues and dynamical system
Eigen values are motivated by an applied to discrete and continuous dynamical systems.