## Preface¶

• This is the first tutorial of a series that aims to explain the relationship between causality and G-invariances:
• In this tutorial we consider the design of G-invariant neural networks, which are neural networks invariant to transformations (actions) of a transformation group.

• Target audience:

• Neural network enthusiasts (familiar with neurons and know how to implement a feedforward network)
• Linear algebra enthusiasts (familiar with eigenvectors, sum, multiplication, and vectorization of matrices)