Improve ML docs/tests

[MichaeINeumann]

Describe your change:

• [ ] Add an algorithm?
• [ ] Fix a bug or typo in an existing algorithm?
• [x] Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• [x] Documentation change?

Checklist:

• [x] I have read CONTRIBUTING.md.
• [x] This pull request is all my own work -- I have not plagiarized.
• [x] I know that pull requests will not be merged if they fail the automated tests.
• [ ] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• [x] All new Python files are placed inside an existing directory.
• [x] All filenames are in all lowercase characters with no spaces or dashes.
• [x] All functions and variable names follow Python naming conventions.
• [x] All function parameters and return values are annotated with Python type hints.
• [x] All functions have doctests that pass the automated testing.
• [ ] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• [x] If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

Summary

• improve k-means docstrings/type hints and add convergence doctests
• refactor gradient descent helpers and add targeted unit tests
• add typed linear regression docs/examples and new ML pytest module

Testing

• .venv/bin/pre-commit run --files machine_learning/k_means_clust.py machine_learning/linear_regression.py machine_learning/gradient_descent.py machine_learning/test_machine_learning_algorithms.py
• .venv/bin/python -m pytest machine_learning/test_machine_learning_algorithms.py

Fixes #13919