docs: Optimisation tutorial

[toby-coleman]

Summary

Adds a tutorial demonstrating how to use the Tuner, both in code and via CLI.

Changes

• Tutorial and associated code.
• Updates to MkDocs config to publish documentation on the plugboard.tune submodule.

[gemini-code-assist]

Summary of Changes

Hello @toby-coleman, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new tutorial that guides users on how to use the Tuner class and CLI to optimise process models. It includes updates to the documentation configuration and introduces new parameter specifications for defining tunable model parameters.

Highlights

• New Tutorial: Added a tutorial demonstrating how to use the Tuner, both in code and via CLI, to optimise a process model.
• MkDocs Configuration Update: Updated the MkDocs configuration to publish documentation on the plugboard.tune submodule.
• Parameter Specifications: Introduced CategoricalParameterSpec, FloatParameterSpec, and IntParameterSpec in plugboard.schemas.tune for defining tunable model parameters.

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[gemini-code-assist]

Code Review

This pull request adds a tutorial on optimisation using the Tuner. I have suggested ensuring consistent naming of components and a minor refactoring in the example Python code to improve type safety.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

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