🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

Python Implementation of Reinforcement Learning: An Introduction

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Deep universal probabilistic programming with Python and PyTorch

Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

The Natural Language Decathlon: A Multitask Challenge for NLP

Version control for machine learning

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to …

End-to-end neural table-text understanding models.

Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator suppor…

A bare-bones repository demonstrating how to set up tools for data science projects that will help you write higher quality code.

Chaospy - Toolbox for performing uncertainty quantification.

A toolbox for integrated information theory.

Library for reading and analyzing astrophysical spectral data cubes

Neural generation model for Open Information Extraction

Combine images made with different resolutions, including the "feathering" technique for interferometry data.

Bayesian spectral decomposition and model fitting using Nested Sampling

Signal identification tools (masking and noise) for spectral line data.

Python toolkit for reading the radio astronomy data format known as the Science Data Model (SDM)