Bring parallelization up to PZClassifier

[OliviaLynn]

Problem & Solution Description (including issue #)

Brings parallelization code of UniformBinningClassifier up to parent PZClassifier. (While I'm not making the equal count classifier parallelized as well, that and future classifiers would now be able to run in parallel by implementing their own version of _process_chunk).

Adds in some docstrings to make the process as transparent as possible, and ideally a helpful template for anyone ramping up on rail-style parallelization in the future.

Code Quality

• [x] My code follows the code style of this project
• [x] I have written unit tests or justified all instances of #pragma: no cover; in the case of a bugfix, a new test that breaks as a result of the bug has been added
• [x] My code contains relevant comments and necessary documentation for future maintainers; the change is reflected in applicable demos/tutorials (with output cleared!) and added/updated docstrings use the NumPy docstring format
• [x] Any breaking changes, described above, are accompanied by backwards compatibility and deprecation warnings

[codecov[bot]]

Codecov Report

Attention: Patch coverage is 92.85714% with 2 lines in your changes are missing coverage. Please review.

Project coverage is 97.11%. Comparing base (40802f3) to head (99d3fd8). Report is 2 commits behind head on main.

Files	Patch %	Lines
src/rail/estimation/algos/uniform_binning.py	66.66%	2 Missing :warning:

Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #88 +/- ## ========================================== - Coverage 97.20% 97.11% -0.09% ========================================== Files 32 32 Lines 1755 1770 +15 ========================================== + Hits 1706 1719 +13 - Misses 49 51 +2 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.