feat: Implement Principal Component Analysis (PCA)

[parikshit2111]

• Added PCA implementation with dataset standardization.
• Used Singular Value Decomposition (SVD) for computing principal components.
• Fixed import sorting to comply with PEP 8 (Ruff I001).
• Ensured type hints and docstrings for better readability.
• Added doctests to validate correctness.
• Passed all Ruff checks and automated tests.

Describe your change:

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

Checklist:

• [✅] I have read CONTRIBUTING.md.
• [✅] This pull request is all my own work -- I have not plagiarized.
• [✅] 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.
• [✅] All new Python files are placed inside an existing directory.
• [✅] All filenames are in all lowercase characters with no spaces or dashes.
• [✅] All functions and variable names follow Python naming conventions.
• [✅] All function parameters and return values are annotated with Python type hints.
• [✅] 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.
• 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".

[cclauss]

Awesome!! Thanks for doing this!