seemore Hub
seemore is an educational project that revisits some of the basics of deep learning for computer vision by focusing on implementation and on the theoretical motivation of design choices. As such, a moderate level of familiarity with deep learning is recommended, as we will take much for granted. It is conceptually based on Andrej Karpathy’s makemore, which covers natural language processing instead.
As is tradition, we will do classification on the MNIST dataset, composed of handwritten digits, by considering increasingly complex architectures. Below you can find the roadmap (links are added as new posts are out):
- So, why automatic differentiation?
- Implementing automatic differentiation from scratch
- Creating a multi-layer perceptron without PyTorch
- Convolutions from scratch: road to LeNet-5
- LeNet-5
- Going deeper: introducing ResNets
- InceptionNet, attention-based approaches…?