Awesome Python Data Science

Models, data loaders and abstractions for language processing, powered by PyTorch

Fast, flexible and easy to use probabilistic modelling in Python.

A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Generate embeddings from large-scale graph-structured data.

Datetimes for Humans™

Accelerated deep learning R&D

Tensorforce: a TensorFlow library for applied reinforcement learning

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

NumPy and Pandas interface to Big Data

TensorFlow Reinforcement Learning

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

High performance datastore for time series and tick data

Shōgun

StellarGraph - Machine Learning on Graphs

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

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

Data manipulation and transformation for audio signal processing, powered by PyTorch

Pandas integration with sklearn

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.

Sequential model-based optimization with a `scipy.optimize` interface

POT : Python Optimal Transport

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Learning to Rank in TensorFlow

Adaptive Experimentation Platform

Neural Network Libraries

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

Algorithms for explaining machine learning 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

Algorithms for outlier, adversarial and drift detection

An efficient video loader for deep learning with smart shuffling that's super easy to digest

Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Scrape Twitter for Tweets

An intuitive library to add plotting functionality to scikit-learn objects.

Graph Neural Networks with Keras and Tensorflow 2.

A modular active learning framework for Python

Source-to-Source Debuggable Derivatives in Pure Python

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Reinforcement Learning in PyTorch

Feature engineering and selection open-source Python library compatible with sklearn.

library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization

🏕️ Reproducible development environment for humans and agents

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

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

Open source time series library for Python

A toolkit for reproducible reinforcement learning research.

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.