Examples for ML and deep neural networks in increasing levels of complexity, based off Stanford's CS231n material.
Directory structure:
├── root
│ ├── project1, project 2, ... (organized by common dataset and project goal)
│ │ ├── datasets
│ │ ├── example1, example2, ... (implementations of ML/neural networks, starting from very basic and moving to complex)
│ │ | |── model
│ │ | | |── classifiers
│ │ | | |── (model code)
│ │ | |── (notebooks and utilities)