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The core machine learning library for Skyulf.

Project description

Skyulf Core

Skyulf Core (skyulf-core) is the standalone machine learning library that powers the Skyulf MLOps platform. It provides a robust, type-safe, and modular set of tools for:

  • Data Preprocessing: A comprehensive suite of transformers for cleaning, scaling, encoding, and feature engineering.
  • Modeling: Unified interfaces for classification and regression models, wrapping Scikit-Learn and other libraries.
  • Pipeline Management: Tools to build, serialize, and execute complex ML pipelines.
  • Tuning: Advanced hyperparameter tuning capabilities with support for Grid Search, Random Search, and Optuna.
  • Evaluation: Standardized metrics and evaluation schemas for model performance tracking.

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Website & Documentation

Visit the full documentation and project site for guides, API reference, and examples:

Installation

pip install skyulf-core

Features

  • Type-Safe: Built with modern Python type hints and Pydantic models.
  • Modular: Use only the components you need.
  • Serializable: All components are designed to be easily serialized for storage and deployment.
  • Extensible: Easy to extend with your own custom transformers and models.

License

This project is licensed under the terms of the Apache 2.0 license.

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