Add sprint proposal for Feature-engine modernization

src/content/sprints/feature-engine-sprint-proposal.md

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+---
+title: "Feature-engine"
+numberOfPeople: "10" # How many people you expect to be able to accommodate.
+pythonLevel: "Any" # Any, Beginner, Intermediate, or Advanced.
+contactPerson: # The main person to reach out to regarding the sprint.
+  name: "Soledad Galli"
+  email: "solegalli@protonmail.com"
+  github: "solegalli"
+  twitter: "Soledad_Galli"
+links: # Add as many links as relevant.
+  - title: "Feature-engine's GitHub repo"
+    url: "https://github.com/feature-engine/feature_engine"
+---
+
+# Modernising Feature-engine: Evolving the API for a Changing Python Ecosystem
+
+## Introduction
+
+Feature-engine was originally designed to bridge the gap between pandas and
+scikit-learn at a time when scikit-learn only accepted NumPy arrays. Its design
+decisions were intended to guide users towards good practices by raising errors
+when transformers were used in inappropriate contexts.
+
+The Python machine learning ecosystem has evolved considerably since then.
+Scikit-learn now supports pandas natively, Polars has become a popular dataframe
+library, and users users have requested greater flexibility from Feature-engine
+transformers. To ensure the project continues to meet the needs of its users,
+its API needs to evolve while preserving backward compatibility as much as
+possible.
+
+During this sprint, we will work on implementing the next generation of
+Feature-engine's API, making it more flexible, faster, and compatible with
+modern data processing libraries, while maintaining backward compatibility
+wherever possible.
+
+## Sprint Activities
+
+Participants will work together on the following improvements:
+
+- **Modernise the dataframe API** by adding support for Polars while allowing
+  users to choose the installation that best suits their needs: a pandas-only
+  installation, a Polars-only installation, or support for both backends.
+
+- **Extend flexible error handling across the library.** The variable selection
+  utilities already allow users to choose between raising an error or continuing
+  when conditions are not met. During the sprint, we will extend this behaviour
+  to the transformers so that users can opt for stricter or more permissive
+  workflows.
+
+- **Introduce configurable behaviour for transformation-specific errors.** For
+  example, transformers that apply logarithmic transformations currently fail
+  when negative values are present. We will extend the API to provide suitable
+  options that allow the transformation to continue when appropriate, instead of
+  raising an exception.
+
+- **Improve performance by modernising internal implementations.** Where
+  possible, we will replace pandas operations with equivalent NumPy
+  implementations to improve execution speed while preserving the existing
+  public API and maintaining backward compatibility as much as possible.
+
+- **Write tests and documentation** for the new functionality to ensure
+  reliability and provide clear guidance for users adopting the updated API.
+
+The sprint is suitable for contributors interested in machine learning
+libraries, API design, testing, documentation, and open source development.