Linear Transformations

After completing this course, learners will be able to: represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc.; apply common vector and matrix algebra operations like dot product, inverse, and determinants; express certain types of matrix operations as linear [...]

Concepts in Linear Algebra. One of the most interesting topics to visualize in Linear Algebra are Eigenvectors and Eigenvalues. Here you will learn how to easily calculate them and how they are applicable and particularly interesting when it comes to machine learning implementations.

Learn mathematical methods for data analysis including mathematical formulations and computational methods. Some well-known machine learning algorithms such as k-means are introduced in the examples.