Stanford CS231n Deep Learning for Computer Vision is a graduate course taught at Stanford by Fei-Fei Li and her team. Lecture notes, slides and assignments are free at cs231n.stanford.edu, and the videos of a recent term have been published on Stanford Online’s YouTube channel.
What’s in it? Image classification, training neural networks, convolutional networks and their architectures, sequence models and attention, generative models, object detection and segmentation.
Why we recommend it: Although its name says “vision”, the course builds the foundations of deep learning very solidly. The lecture notes in particular are one of the clearest explanations of the convolution we described with a torch in our CNN post. It’s also a good basis for work that turns EEG into topographic maps and classifies them with CNNs.
Who is it for? Anyone with Python and basic linear algebra who wants to learn deep learning through hands-on assignments.
- Course page: Stanford CS231n