At our January meeting, I presented on Linear Algebra basics in R. I have been taking the Andrew Ng’s Stanford Machine Learning course. That course primarily uses Matlab (or Octave, and open source equivalent), and machine learning involves manipulating and calculating with matrices. Naturally, being an R person, I have been working with some of the techniques in R.

In order to limit the scope of the talk, I focused on matrices, vectors and basic operations with them. There is a practical example that uses a machine learning algorithm, but it’s just to show how R handles a more involved equation with matrices. The talk is not an attempt to teach machine learning.

The slides are available here, and comments or suggestions are welcome.