I recently had the chance to teach a small introductory workshop to the basics of deep learning for the graduate students of the comp2psych doctoral program as well as the lifespan psychology research center of the Max Planck Institute for Human Development.
You can find a fully reproducible version of this course at:
This repository contains a reproducible course on the basics of deep learning. Each topic is covered in a separate Jupyter notebook; each notebook contains theoretical introduction to its topic as well as a practical exercise. For a general introduction to the Jupyter environment, I recommend this tutorial.
So far, this course covers the very basics of deep learning. However, I am planning to extend this course over time by adding more advanced deep learning topics. Each course topic is covered in a separate Jupyter notebook; Each notebook contains theoretical introduction to its topic as well as a practical exercise.
You can either run the Jupyter notebooks locally on your personal computer (see the installation instructions on the course's GitHub page) or remotely with Jupyter Binder using the following link: https://mybinder.org/v2/gh/athms/deep-learning-basics/HEAD
I hope you enjoy the contents of this course. If you have any feedback, please email me (email@example.com) or create a pull request (ideally adhering to these guidelines)