In case it’s helpful we’ve been building some

hamilton tutorials

in an aptly named repository called https://github.com/DAGWorks-Inc/hamilton-tutorials. The idea is to help give some ideas/ways to structure/iterate on Hamilton code to accomplish something. They are

notebook

focused because that’s an easy way to wrap documentation and code. For example, you can run them in google collab easily. https://github.com/DAGWorks-Inc/hamilton-tutorials/tree/main/2023-10-09 is the latest version. It contains three directories: • one for PDF summarization - i.e. LLM workflow to summarize a PDF. ◦ contains a single notebook that walks through some ways to build a LLM workflow. • one for the Titanic Data set - i.e. a data/feature engineering + ML pipeline workflow ◦ contains two notebooks ▪︎ one walks through data & feature engineering. ▪︎ the other fitting a statistical model and builds off the first. (FYI the model isn’t sophisticated). • one for some Hamilton reference code snippets ◦ this should mirror what’s in the docs, but it could be useful for you to save time looking something up. Pull requests/comments/issues suggestions welcome.