Awesome Python Data Science

A game theoretic approach to explain the output of any machine learning model.

Statsmodels: statistical modeling and econometrics in Python

An elegant PyTorch deep reinforcement learning library.

A unified framework for machine learning with time series

AutoML library for deep learning

Automatic extraction of relevant features from time series:

A Python implementation of global optimization with gaussian processes.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

An open source python library for automated feature engineering

A scikit-learn compatible neural network library that wraps PyTorch

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

A highly efficient implementation of Gaussian Processes in PyTorch

Bayesian optimization in PyTorch

NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

Automatic architecture search and hyperparameter optimization for PyTorch

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

Machine Learning toolbox for Humans

A library of metrics for evaluating recommender systems

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