Mathematics for Machine Learning: Linear Algebra


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.

Read more.

Career Relevance by Data Role

The techniques and tools covered in Mathematics for Machine Learning: Linear Algebra are most similar to the requirements found in Data Scientist job advertisements.

Similarity Scores (Out of 100)

Learning Sequence

Online Tutorials
4 weeks

22. Version Control with Git

By Richard Kalehoff

Level: BeginnerGit
Subscribe for updates and new courses
Or create a account
Fast Facts


AlgorithmsApplied MathematicsData ScienceData SetsFunctionsImage AnalysisMachine LearningProduct Analytics

Similar Opportunities
Data Analytics Foundations for Accountancy II

Coursera - University of Illinois at Urbana-Champaign

Signals, Systems, and Learning

edX - Rice University