This repository has been created to serve as an example of how to structure a python repository for an AI/ML project. All ML code is taken and freely adapted from the ML From Scratch project. The current starting-point branch provides the basics: a raw requirements.txt file, a couple of python scripts that simulate typical ML code, this README and some data. During the tutorial several concepts will be shown, such as how to use a virtual environment, how to use a package manager to manage dependencies, how to structure project folders and imports, how to manage configuration, how to setup logging and how to package the code in a standalone module.
Feel free to go to the main branch to see the final form of the repo, or to browse through tags to see some of the intermediate results.