End-to-End Speech Processing Toolkit

Notebooks about Bayesian methods for machine learning

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines

Source code to reproduce experiments from the article Practitioner’s Guide to Statistical Tests

Open MMLab Detection Toolbox and Benchmark

A hyperparameter optimization framework

Third place solution to the "University of Liverpool - Ion Switching" Kaggle competition

WTFML: Well That's Fantastic Machine Learning

An interactive deep learning book with code, math, and discussions, based on the NumPy interface.

This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/en-us/python/azure/ or …

Learning embeddings for classification, retrieval and ranking.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Model Serving on PyTorch

Enabling PyTorch on Google TPU

covidAsk: Answering Domain-Specific Questions in Real-Time for COVID-19

Papers & presentations from Hugging Face's weekly science day

XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.

Pytorch framework for doing deep learning on point clouds.

Time Series Forecasting Best Practices & Examples

State of the Art Natural Language Processing

🤖⚡ Daily scikit-learn tips

TensorFlow code and pre-trained models for BERT