Module 03
Math for data science
Vectors, matrices and the linear transformations underneath every model you will train — worked in NumPy rather than on paper.
Outcome
What you will be able to do
You can reason about data as vectors and matrices, and implement the operations models rely on with NumPy.
Lessons
Work through these in order
- 01VectorsAt its simplest, a vector is a numeric element that has both magnitude and direction. The magnitude represents a distance (for example, "2 miles") and the direction indicates which way the vector is… 8 min
- 02Introduction to MatricesA matrix arranges numbers into rows and columns, like this: 8 min
- 03Matrix TransformationsMatrix decompositions are a useful tool for reducing a matrix to their constituent parts in order to simplify a range of more complex operations. Perhaps the most used type of matrix decomposition is… 8 min
Assessment
Module quiz — 70% to pass
6 questions mixing concept checks and short code-output problems. Graded on the server with per-question explanations afterwards, unlimited retakes, and a badge with a verification code the moment you pass.