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

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

Bayesian optimization in PyTorch

Generate embeddings from large-scale graph-structured data.

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

Datetimes for Humans™

Accelerated deep learning R&D

Tensorforce: a TensorFlow library for applied reinforcement learning

Python Toolkit for Causal and Probabilistic Reasoning

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

The machine learning toolkit for time series analysis in Python

TensorFlow Reinforcement Learning

Visualize and compare datasets, target values and associations, with one line of code.

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/

With Holoviews, your data visualizes itself.

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

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

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.

POT : Python Optimal Transport

Neural Network Libraries

Learning to Rank in TensorFlow