binary crossentropy loss function added

[TMGA-WAY]

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".

[tianyizheng02]

We already have the binary cross entropy loss in machine_learning/loss_functions.py. It's the very first function in the file. Please make sure to check the codebase for an algorithm before contributing in order to avoid contributing a duplicate.