In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.

This course is part of the Mathematics for Machine Learning Specialization

**308,955**already enrolled

Offered By

## About this Course

## Skills you will gain

- Eigenvalues And Eigenvectors
- Basis (Linear Algebra)
- Transformation Matrix
- Linear Algebra

## Offered by

## Syllabus - What you will learn from this course

**2 hours to complete**

### Introduction to Linear Algebra and to Mathematics for Machine Learning

**2 hours to complete**

**2 hours to complete**

### Vectors are objects that move around space

**2 hours to complete**

**3 hours to complete**

### Matrices in Linear Algebra: Objects that operate on Vectors

**3 hours to complete**

**7 hours to complete**

### Matrices make linear mappings

**7 hours to complete**

## Reviews

- 5 stars74.70%
- 4 stars19.73%
- 3 stars3.40%
- 2 stars1.14%
- 1 star1%

### TOP REVIEWS FROM MATHEMATICS FOR MACHINE LEARNING: LINEAR ALGEBRA

This is a great course to built foundation for Machine Learning. Both the lecturers are amazing and great use of technology in presenting the concepts. Great example linked to PageRank algorithm.

The content of the course is very relevant, and the instructors are really fun and helpful.My only suggestion is to upload revisions for each assessment, so we can understand what we are doing wrong.

The concepts are explained well. However, might not be very useful for people who have some basic understanding of linear algebra. Taking this course is not as effective as reading the textbook.

This was a terrific course; the instructors' are passionate and knowledgeable about the course material, the assignments are engaging and relevant, and the length of the videos feels "just right".

## About the Mathematics for Machine Learning Specialization

## Frequently Asked Questions

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