MISSION 162

Matrix Algebra

In the previous vectors lesson, we learned about vectors and the different properties of vectors. Similar to vectors, matrices have their own set of algebraic operations.

In this lesson, we'll learn the core matrix operations and build up to using them to solve a matrix equation. You'll learn concepts such as row operations or mathematical operations that you can perform on the rows of a matrix. We'll also discuss what it means to multiply matrices, take the transpose of a matrix, as well as the inverse of a matrix. 

After learning of those concepts, we will walk through the steps of solving a matrix equation.

Towards the end of the mission, we will talk about how to find the determinant and matix inverse for matrices of higher dimensions so you can compute the determinant and the inverse of a complex matrix without feeling lost.

As you work through each concept, you’ll get to apply what you’ve learned from within your browser so that there's no need to use your own machine to do the exercises. The Python environment inside of this course includes answer checking so you can ensure that you've fully mastered each concept before learning the next concept.

Objectives

  • Learn how to perform matrix operations in NumPy.
  • Learn about the matrix inverse and transpose.
  • Learn how to solve the matrix inverse in higher dimensions.

Mission Outline

1. Basic Matrix Operations
2. Matrix Vector Multiplication
3. Matrix Multiplication
4. Matrix Transpose
5. Identity Matrix
6. Matrix Inverse
7. Solving The Matrix Equation
8. Determinant For Higher Dimensions
9. Matrix Inverse For Higher Dimensions
10. Next Steps
11. Takeaways

linear-algebra-for-machine-learning

Course Info:

Beginner

The median completion time for this course is 5.4 hours. View Details

This course requires a premium subscription. This course includes four missions. It is the 20th course in the Data Scientist in Python path.

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