High performance ML library with XGBoost implementation in pure Python
Project description
cortado: high performance 100% Python package for machine learning
Main features:
- native support for both numeric and categorical data
- innovative feature engineering: virtual data columns and easy conversions between numeric and categorical data
- out of core data processing: process dataframes bigger than RAM
- implementation of XGBoost logistic in 500 lines of Python code, faster than original C++ implementation (using Numba jit under the hood)
- easy to extend, written in functional style for easy composition
- works well with pandas dataframes
Demo notebooks:
- intro
Project details
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