Course Format
I teach a course on deep neural networks for Washington University in St. Louis. You can find links to my new course’s full content at the course website:
- T81-558:Applications of Deep Neural Networks (current version)
- Textbook
- My YouTube Channel - All the videos are posted here.
- Play List for the Course - All the videos are posted here.
I always make updates to the course videos (it is taught in a hybrid format). To stay up to date, join my YouTube channel:
Course Textbook
The course text book is “Applications of Deep Neural networks with Keras“, ISBN 9798416344269.
For the General Public (non-WUSTL Students)
All of the course material is online, this is a hybrid course. Use my GitHub repo as the main index for the course. The students are graded on 10 coding assignments, mid-term exam, Kaggle, and final project. The 10 coding assignments are all graded by an automatic process. Supporters of my Patreon are given an API-Key to access the autograder for the 10 coding assignments. However, only actual WUSTL students access the MidTerm and final projects. Obviously, only WUSTL students are given college credit for this course.
Older Stuff
If you are interested in my older course material, you can find it on YouTube. I originally created two neural network online courses back in 2009. The material contained in those courses is somewhat outdated in the deep learning era.
- 2016 Version Playlist - This is the 2016 version of my class, when I first started teaching it at WashU. These are literally screencasts of when I lectured in a classroom.
- 2009 Version Playlist Java - This is a really old version that I recorded in a spare bedroom! This is all pre-deep learning stuff. (Java version)
- 2009 Version Playlist C# - This is a really old version that I recorded in a spare bedroom! This is all pre-deep learning stuff. (Java version)