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Library for machine learning stacking generalization.

Pandas-based utility to calculate weighted means, medians, distributions, standard deviations, and more.

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.

A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).

A library for hidden semi-Markov models with explicit durations

SigOpt wrappers for scikit-learn methods

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

Build, test, deploy, iterate - Dev and prod tool for data science pipelines

a feature engineering wrapper for sklearn

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Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University

Auralisation of learned features in CNN (for audio)

scikit-learn addon to operate on set/"group"-based features

Universal 1d/2d data containers with Transformers functionality for data analysis.

Machine learning on dirty tabular data (legacy clone of skrub)

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A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering 🛠

TensorLight - A high-level framework for TensorFlow

Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.