## Fundamental Course in Linear Algebra for Machine Learning, Data Science, Computer Science and Electrical Engineering

**HOW INTRODUCTION TO LINEAR ALGEBRA |MATRICES| IS SET UP TO MAKE COMPLICATED LINEAR ALGEBRA EASY**

This course deals with concepts required for the study of Machine Learning and Data Science. Matrices is a fundamental of the Theory of Linear Algebra. Linear Algebra is used in Machine Learning, Data Science, Computer Science and Electrical Engineering.

This 48+ lecture course includes video explanations of everything from Fundamental of Matrices, and it includes more than 45+ examples (with detailed solutions) to help you test your understanding along the way. Introduction To Linear Algebra |MATRICES| is organized into the following sections:

- Introduction
- Types of Matrices
- Difference between a Matrix and a Determinant
- Operations on Matrices
- Various Kinds Of Matrices
- Adjoint of a Square Matrix
- Elementary Row and Column Transformation
- Inverse of a Matrix
- Echelon Form and Normal Form of a Matrix
- Rank of a Matrix
- Solution of Simultaneous Linear Equations
- The Reflection Matrix
- Rotation Through an Angle Theta

Summary

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Brand Name

UDEMY

Course Name

Introduction To Linear Algebra |MATRICES|

Price

USD 110

Product Availability

Available in Stock

Introduction To Linear Algebra |MATRICES|