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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
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Brand Name
UDEMY
Course Name
Introduction To Linear Algebra |MATRICES|
Price
USD 110
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Available in Stock
Introduction To Linear Algebra |MATRICES|
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