Dataeval

🌟 **Feature Release**
- `a0b04800` - Refactor DataEval functions and classes and update documentation

- Changes DataEval functions and classes to be more hierarchical in modules:
- detectors
- drift (DriftCVS, DriftKS, DriftMMD, DriftUncertainty)
- linters (Clusterer, Duplicates, Outliers)
- ood (OOD_AE, OOD_AEGMM, OOD_LLR, OOD_VAE, OOD_VAEGMM)
- flags (ImageStat)
- metrics
- bias (balance, coverage, diversity, parity)
- estimators (ber, divergence, uap)
- stats (imagestats, channelstats)
- workflows (Sufficiency)
- Backends have been moved from `models` to `tensorflow` and `torch`
- Renamed following classes:
- `Linter` -> `Outliers`
- `parity` -> `label_parity`
- `parity_metadata` -> `parity`
- `DriftOutput` -> `DriftBaseOutput`
- `DriftUnivariateOutput` -> `DriftOutput`
- Miscellaneous fixes:
- Documentation updated
- Streamlined optional import checks in the `__init__.py` tree
- Fixed misspelling in glossary

👾 **Fixes**
- `84aae760` - balance test cleanup

📝 **Miscellaneous**
- `6d09d710` - Add CONTRIBUTING.md
- `72387d9c` - Updated version replacement script to include cache files
- `5285f01b` - Prototype Performance Estimation
- `3ae16116` - concept pages for balance and diversity, rescale Simpson diversity
- `3e16a905` - Switching documentation themes to the pydata theme
- `d50d9cd1` - Update Landing Page
- `2fd7fa59` - Author drift detection tutorial
- `49b5af42` - Use uv instead of pyenv for python deployment
- `0f6eb6b0` - Pin notebooks on release to specific version
- `4f101a4e` - Adjust imagestats and channelstats reference guides to new format
- `0ee82ede` - Only build data image in main pipeline
- `7b84ceb5` - Improve test coverage
- `d3c5258a` - Add StatsOutput as input type for linter and duplicates
- `cf73393a` - Updates drift reference guides and concept page
- `4ce5cdf7` - Adjust model reference guides to new format
- `17195a2b` - Adjust parity reference guides to new format
- `e9761b4d` - Adjust out of distribution reference guides to new format
- `eaf707a7` - Adjust uap reference guide to new format
- `335ac3be` - Adjust sufficiency reference guide to new format
- `3a866f01` - Change Optional[Type] to Type | None per 3.10+ standards

🌟 **Feature Release**
- `a0b04800` - Refactor DataEval functions and classes and update documentation

- Changes DataEval functions and classes to be more hierarchical in modules:
- detectors
- drift (DriftCVS, DriftKS, DriftMMD, DriftUncertainty)
- linters (Clusterer, Duplicates, Outliers)
- ood (OOD_AE, OOD_AEGMM, OOD_LLR, OOD_VAE, OOD_VAEGMM)
- flags (ImageStat)
- metrics
- bias (balance, coverage, diversity, parity)
- estimators (ber, divergence, uap)
- stats (imagestats, channelstats)
- workflows (Sufficiency)
- Backends have been moved from `models` to `tensorflow` and `torch`
- Renamed following classes:
- `Linter` -> `Outliers`
- `parity` -> `label_parity`
- `parity_metadata` -> `parity`
- `DriftOutput` -> `DriftBaseOutput`
- `DriftUnivariateOutput` -> `DriftOutput`
- Miscellaneous fixes:
- Documentation updated
- Streamlined optional import checks in the `__init__.py` tree
- Fixed misspelling in glossary

🛠️ **Improvements and Enhancements**
- `5f730baa` - Refactor ImageStats and ChannelStats as metric functions

👾 **Fixes**
- `84aae760` - balance test cleanup
- `3ebd278c` - handle float-type categorical variables in balance metric
- `066b7153` - Fixes modzscore to account for division by 0

📝 **Miscellaneous**
- `d50d9cd1` - Update Landing Page
- `2fd7fa59` - Author drift detection tutorial
- `49b5af42` - Use uv instead of pyenv for python deployment
- `0f6eb6b0` - Pin notebooks on release to specific version
- `4f101a4e` - Adjust imagestats and channelstats reference guides to new format
- `0ee82ede` - Only build data image in main pipeline
- `7b84ceb5` - Improve test coverage
- `d3c5258a` - Add StatsOutput as input type for linter and duplicates
- `cf73393a` - Updates drift reference guides and concept page
- `4ce5cdf7` - Adjust model reference guides to new format
- `17195a2b` - Adjust parity reference guides to new format
- `e9761b4d` - Adjust out of distribution reference guides to new format
- `eaf707a7` - Adjust uap reference guide to new format
- `335ac3be` - Adjust sufficiency reference guide to new format
- `3a866f01` - Change Optional[Type] to Type | None per 3.10+ standards
- `fe1e292d` - Use output dataclass with metadata
- `b3f6a027` - Unify handling of image reshaping

🛠️ **Improvements and Enhancements**
- `5f730baa` - Refactor ImageStats and ChannelStats as metric functions

👾 **Fixes**
- `3ebd278c` - handle float-type categorical variables in balance metric
- `066b7153` - Fixes modzscore to account for division by 0

📝 **Miscellaneous**
- `fe1e292d` - Use output dataclass with metadata
- `b3f6a027` - Unify handling of image reshaping

🌟 **Feature Release**
- `bea0446c` - Torch Dataset Reader

🛠️ **Improvements and Enhancements**
- `eda88822` - Refactor metrics

📝 **Miscellaneous**
- `a4b8e919` - Created new documentation issue templates
- `1028d082` - Remove is_arraylike function
- `dbcecec6` - Refactored read_dataset to handle common dataset returns
- `61b1f854` - Updated Workflow Landing Page
- `cf96c7f2` - Run doctest in CI pipeline
- `ecfcf89b` - Adjusted notebooks to work on google colab and added environment requirements
- `5f863782` - Update remaining metric output to NamedTuple
- `e58f4dba` - Add metadata parity documentation
- `6319a1d4` - Adding Duplicates concept
- `787545f5` - Adding ImageStats and ChannelStats concept document
- `7826405c` - Update Data Cleaning concept
- `50047116` - Change to Semantic Versioning
- `9e43399c` - Bayes Error Rate - explanation documentation
- `266ad738` - Updated BER docstrings with NDArray, shapes, and examples

🛠️ **Improvements and Enhancements**
- `3225cf18` - Convert remaining metrics and detectors to ArrayLike
- `5d88b82a` - Add Torch and Tensorflow interop through ArrayLike protocol and to_numpy converter
- `d3342275` - Refactor linter and duplicates to call evaluate with data
- `65d5aaa8` - Refactor metrics to call evaluate with data

DAML is now officially rebranded as DataEval! New name, same great camel flavor.