The goal of this project is to introduce a selection of canonical neural network models of cognition. Each section covers the following contents:

• Historical and theoretical background
• Mathematical formaliation
• Code implementation in Python
• Example application
• Model limitations

Models are implemented in Python as Jupyter Notebooks tutorials. Although is recommended to follow the tutorials in a linear fashion, they can be used as stand-alone learning material.

The tutorials are intended to be used by beginner to intermediate level students and/or researchers in cognitive science or related fields, for instance, advance undergraduates or early-stage graduate students. Knowledge of Python is not required, but it is advised to have previous exposure/experience working with some dynamically typed programming language like R, Julia, Scala, or Matlab.