Added Binary Focal Cross Entropy

[ank426]

Describe your change:

Added Binary Focal Cross Entropy loss function. It's a variation of binary cross-entropy that addresses class imbalance by
focusing on hard examples.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• 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".

[ank426]

@tianyizheng02 Could you please review this?

[tianyizheng02]

All loss function files were consolidated into machine_learning/loss_functions.py in #10737. Could you move your new code into that file?

[ank426]

All loss function files were consolidated into machine_learning/loss_functions.py in #10737. Could you move your new code into that file?

Done.

[tianyizheng02]

Thanks for your contribution!