CourseNatural Language Processing: The Complete Course · Module 11: Capstone · part 73 of 73
Part 73 · Module 11: Capstone

Lab: The Tidewell inbox service, end to end

177 min read·14 Oct 2026
Module 11 · Capstone lab · About 120 minutes · Needs: the labs of Modules 1 to 10 (or their cells, pasted here). CPU only; a Groq or Gemini key only for the LLM track

What you are building

message clean language redact route extract suggest summarise record one each each job: the cheapest method that meets Rosa's bar
Every job is one function (blue); redaction keeps the record safe to store (green); routing may abstain to Ines (amber); one record comes out (green).

It is Monday 16 November 2026, project week 11, and Rosa signs off the service today. Ten labs left ten pieces in tidewell-inbox/. This lab joins them into process(message, parts): one message in, one record out, all five jobs done. For each job it keeps the cheapest method that meets Rosa's bar, chosen from three build tracks: classical, transformer and LLM, the last switched off and checked with scripted stand-ins. The evidence is shared: per-language scores on HARD_TEST, a cost and latency table measured on this CPU, and the name-swap check.

The hand-over follows a published idea. Margaret Mitchell and colleagues, in "Model Cards for Model Reporting" (FAT* 2019, arXiv:1810.03993), proposed shipping a model with a short document: what it is for and not for, how it was evaluated, its results by group and condition, and its known limits. Your MODEL_CARD.md follows that idea.

Open a new Colab notebook, call it module-11-capstone.ipynb, and run each cell in order.

The rest of this part opens with an account

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