# Linear Algebra for Data Science & Machine Learning - 2020

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**Description**

**LINEAR ALGEBRA for DATA SCIENCE & MACHINE LEARNING** **COURSE DESCRIPTION**

Why Learn Linear Algebra?

Sets

Linear Equation Systems

What is a Scalar?

Scalar & Vector Arithmetic

Vector Addition and Subtraction

Scalar Multiplication of Vectors

Dot & Cross Product

Dot Product Linear Algebra Style

Vector Subspace

Linear Combinations of Vectors

Span

Linear Dependence and Independence

Solving Systems of linear equations

Linear Equation Example

Generating Set and Basis

Linear Mapping/Linear Transformation

Additivity

Homogeneity

Kernel

Matrices - Tensors

Matrix Multiplication

Range of a Matrix

Kernel of a Matrix

Determinant of a Matrix

Identity , Transpose and Inverse Matrix

Eigenvector and Eigenvalue

**WHY LINEAR ALGEBRA?**

Linear algebra is absolutely key to understanding the calculus and statistics you need in machine learning and data science.

If you can understand machine learning methods at the level of vectors and matrices you will improve your intuition for how and when they work.

A deeper understanding of the algorithm and its constraints will allow you to customize its application and better understand the impact of tuning parameters on the results.

**THE OPPORTUNITIES YOU WILL HAVE WITH THIS COURSE**

**In-class support:**We don't just give you video lessons. We have created a professional Python Programmer team and community to support you. This means that you will get answers to your questions within 24 hours.

**WHO WE ARE: DATAI TEAM ACADEMY**

DATAI TEAM is a team of Python Programmers and Data Scientists.

**Let's register for the course and start to Linear Algebra for Data Science & Machine Learning.**