Introduction to Neural Network Models of Cognition - Online Book
On-line interactive book introducing the history, theory, and math of Neural Network Models with Python, from a Cog Science perspective.
neural-networks convolutional-neural-networks recurrent-neural-networks deep-learning article code tutorial

This project is complete. It may serve as a one semester course material for advance undergraduates or early-stage graduate students, which are interested in neural networks and deep learning from a cognitive science perspective.

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.

Don't forget to tag @pabloinsente in your comment, otherwise they may not be notified.

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Psychology PhD student at UW-Madison
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