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mlxtras is a machine learning utility library for feature engineering, model validation, reporting, and MLflow logging.

Project description

mlxtras

mlxtras is a machine learning utility library for feature engineering, model validation, reporting, and MLflow experiment tracking. It provides reusable helpers for pandas, scikit-learn, LightGBM, and time-series workflows.

How it started

This library began as a personal project to learn Python packaging and create reusable tools for common machine learning workflows. It is designed to help you iterate quickly on baselines, validate models, and standardize data science tasks.

Features

  • Feature selection and model validation utilities
  • Time series feature engineering and plotting helpers
  • Ensemble and reporting utilities
  • MLflow experiment logging helpers
  • Data validation and preprocessing tools

Installation

You can install mlxtras using pip:

pip install mlxtras

Acknowledgments

  • ChatGPT Handled documentations of our .md files most of the times.
  • Inspired by work at AirQo
  • Built on top of scikit-learn, pandas, and NumPy

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