Merge branch 'main' into feature/multiclass_confusion_matrix

# Conflicts:
#	docs/tutorials/performance_estimation/multiclass_performance_estimation.rst

Author: nnansters

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.9.0
+current_version = 0.9.1
 commit = True
 tag = True
 

.pre-commit-config.yaml

@@ -38,3 +38,4 @@ repos:
           - types-python-dateutil
           - types-click
           - sqlmodel
+          - types-requests

CHANGELOG.md

@@ -4,6 +4,25 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.9.1] - 2023-07-12
+
+### Changed
+
+- Updated Mendable client library version to deal with styling overrides in the RTD documentation theme
+- Removed superfluous limits for confidence bands in the CBPE class (these are present in the metric classes instead)
+- Threshold value limiting behaviour (e.g. overriding a value and emitting a warning) will be triggered not only when
+the value crosses the threshold but also when it is equal to the threshold value. This is because we interpret the
+threshold as a theoretical maximum.
+
+### Added
+
+- Added a new example notebook walking through a full use case using the NYC Green Taxi dataset, based on the blog of [@santiviquez](https://github.com/santiviquez)
+
+### Fixed
+
+- Fixed broken Docker container build due to changes in public Poetry installation procedure
+- Fixed broken image source link in the README, thanks [@NeoKish](https://github.com/NeoKish)!
+
 ## [0.9.0] - 2023-06-26
 
 ### Changed

Dockerfile

@@ -36,7 +36,7 @@ RUN apt-get update && \
     build-essential
 
 # Install Poetry - respects $POETRY_VERSION & $POETRY_HOME
-RUN curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py | python
+RUN curl -sSL https://install.python-poetry.org | python3 - --version $POETRY_VERSION
 ENV PATH="$POETRY_HOME/bin:$PATH"
 
 # Import our project files

README.md

@@ -71,15 +71,15 @@ Allowing you to have the following benefits:
 | 🔬 **[Technical reference]**                                                                                    | Monitor the performance of your ML models.                                             |
 | 🔎 **[Blog]**                                                                                                   | Thoughts on post-deployment data science from the NannyML team.                        |
 | 📬 **[Newsletter]**                                                                                             | All things post-deployment data science. Subscribe to see the latest papers and blogs. |
-| 💎 **[New in v0.9.0]**                                                                                          | New features, bug fixes.                                                               |
+| 💎 **[New in v0.9.1]**                                                                                          | New features, bug fixes.                                                               |
 | 🧑‍💻 **[Contribute]**                                                                                             | How to contribute to the NannyML project and codebase.                                 |
 | <img src="https://raw.githubusercontent.com/NannyML/nannyml/main/media/slack.png" height='15'> **[Join slack]** | Need help with your specific use case? Say hi on slack!                                |
 
 [nannyml 101]: https://nannyml.readthedocs.io/en/stable/
 [performance estimation]: https://nannyml.readthedocs.io/en/stable/how_it_works/performance_estimation.html
 [key concepts]: https://nannyml.readthedocs.io/en/stable/glossary.html
 [technical reference]: https://nannyml.readthedocs.io/en/stable/nannyml/modules.html
-[new in v0.9.0]: https://github.com/NannyML/nannyml/releases/latest/
+[new in v0.9.1]: https://github.com/NannyML/nannyml/releases/latest/
 [real world example]: https://nannyml.readthedocs.io/en/stable/examples/california_housing.html
 [blog]: https://www.nannyml.com/blog
 [newsletter]: https://mailchi.mp/022c62281d13/postdeploymentnewsletter
@@ -100,7 +100,7 @@ NannyML can also **track the realised performance** of your machine learning mod
 
 To detect **multivariate feature drift** NannyML uses [PCA-based data reconstruction](https://nannyml.readthedocs.io/en/main/how_it_works/data_reconstruction.html). Changes in the resulting reconstruction error are monitored over time and data drift alerts are logged when the reconstruction error in a certain period exceeds a threshold. This threshold is calculated based on the reconstruction error observed in the reference period.
 
-<p><img src="https://raw.githubusercontent.com/NannyML/nannyml/main/docs/_static/drift-guide-multivariate.svg"></p>
+<p><img src="https://raw.githubusercontent.com/NannyML/nannyml/main/docs/_static/butterfly-multivariate-drift.svg"></p>
 
 NannyML utilises statistical tests to detect **univariate feature drift**. We have just added a bunch of new univariate tests including Jensen-Shannon Distance and L-Infinity Distance, check out the [comprehensive list](https://nannyml.readthedocs.io/en/stable/how_it_works/univariate_drift_detection.html#methods-for-continuous-features). The results of these tests are tracked over time, properly corrected to counteract multiplicity and overlayed on the temporal feature distributions. (It is also possible to visualise the test-statistics over time, to get a notion of the drift magnitude.)
 
@@ -264,11 +264,11 @@ Curious what we are working on next? Have a look at our [roadmap](https://bit.ly
 
 To cite NannyML in academic papers, please use the following BibTeX entry.
 
-### Version 0.9.0
+### Version 0.9.1
 
 ```
     @misc{nannyml,
-        title = {{N}anny{ML} (release 0.9.0)},
+        title = {{N}anny{ML} (release 0.9.1)},
         howpublished = {\url{https://github.com/NannyML/nannyml}},
         month = mar,
         year = 2023,