🎯 Why Skore?
When it comes to data science, you have excellent tools at your disposal: pandas and polars for data exploration, skrub for stateful transformations, and scikit-learn for model training and evaluation. These libraries are designed to be generic and accommodate a wide range of use cases.
But here's the challenge: Your experience is key to choosing the right building blocks and methodologies. You often spend significant time navigating documentation, writing boilerplate code for common evaluations, and struggling to maintain clear project structure.