Awesome Python Data Science

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Sequence learning toolkit for Python

Python package for stacking (machine learning technique)

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Simple structured learning framework for python

Add built-in support for quaternions to numpy

A Free and Open Source Python Library for Multiobjective Optimization

Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!

🎯 A comprehensive gradient-free optimization framework written in Python

QKeras: a quantization deep learning library for Tensorflow Keras

No description.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

Module for statistical learning, with a particular emphasis on time-dependent modelling

Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

This library has moved to https://github.com/googleapis/google-cloud-python/tree/main/packages/pandas-gbq

Directions overlay for working with pandas in an analysis environment

Python implementation of the rulefit algorithm

scikit-learn inspired API for CRFsuite

A Python toolkit for processing tabular data

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

A python package for animating plots build on matplotlib.

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Python library for multilinear algebra and tensor factorizations

🎆 A visualization of the CapsNet layers to better understand how it works

A set of tools for creating and testing machine learning features, with a scikit-learn compatible API

Multiple Pairwise Comparisons (Post Hoc) Tests in Python

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

No description.

PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

Genetic feature selection module for scikit-learn

Solve automatic numerical differentiation problems in one or more variables.

Bayesian Optimization using GPflow

A pure Python implementation of Apache Spark's RDD and DStream interfaces.

zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

Python-based implementations of algorithms for learning on imbalanced data.

A library for augmenting annotated audio data

Relevance Vector Machine implementation using the scikit-learn API.

A fast xgboost feature selection algorithm

Stacked Generalization (Ensemble Learning)

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama

The goal of pandas-log is to provide feedback about basic pandas operations. It provides simple wrapper functions for the most common functions that add additional logs

QML: Quantum Machine Learning

BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

A Genetic Programming platform for Python with TensorFlow for wicked-fast CPU and GPU support.