7059 Repositories
Python data-uncertainty-learning Libraries
🏆 A ranked list of awesome Python open-source libraries and tools. Updated weekly.
Best-of Python 🏆 A ranked list of awesome Python open-source libraries & tools. Updated weekly. This curated list contains 230 awesome open-source pr
DeiT: Data-efficient Image Transformers
DeiT: Data-efficient Image Transformers This repository contains PyTorch evaluation code, training code and pretrained models for DeiT (Data-Efficient
Deploy a ML inference service on a budget in less than 10 lines of code.
BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end.
PORORO: Platform Of neuRal mOdels for natuRal language prOcessing
PORORO: Platform Of neuRal mOdels for natuRal language prOcessing pororo performs Natural Language Processing and Speech-related tasks. It is easy to
Collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning.
Collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning Installation
Learning Continuous Image Representation with Local Implicit Image Function
LIIF This repository contains the official implementation for LIIF introduced in the following paper: Learning Continuous Image Representation with Lo
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
Trankit: A Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing Trankit is a light-weight Transformer-based Pyth
This is a database of 180.000+ symbols containing Equities, ETFs, Funds, Indices, Futures, Options, Currencies, Cryptocurrencies and Money Markets.
Finance Database As a private investor, the sheer amount of information that can be found on the internet is rather daunting.
机器学习、深度学习、自然语言处理等人工智能基础知识总结。
说明 机器学习、深度学习、自然语言处理基础知识总结。 目前主要参考李航老师的《统计学习方法》一书,也有一些内容例如XGBoost、聚类、深度学习相关内容、NLP相关内容等是书中未提及的。
Python AsyncIO data API to manage billions of resources
Introduction Please read the detailed docs This is the working project of the next generation Guillotina server based on asyncio. Dependencies Python
⚾🤖⚾ Automatic baseball pitching overlay in realtime
⚾ Automatically overlaying pitch motion and trajectory with machine learning! This project takes your baseball pitching clips and automatically genera
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN
artificial intelligence cosmic love and attention fire in the sky a pyramid made of ice a lonely house in the woods marriage in the mountains lantern
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin
🛠️ Learn a technology X by doing a project - Search engine of project-based learning
Learn X by doing Y 🛠️ Learn a technology X by doing a project Y Website You can contribute by adding projects to the CSV file.
Implementation of the Point Transformer layer, in Pytorch
Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
WILDS is a benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications, from tumor identification to wildlife monitoring to poverty mapping.
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
RLStructures is a library to facilitate the implementation of new reinforcement learning algorithms.
RLStructures is a lightweight Python library that provides simple APIs as well as data structures that make as few assumptions as possibl
Script utilizando OpenCV e modelo Machine Learning para detectar o uso de máscaras.
Reconhecendo máscaras Este repositório contém um script em Python3 que reconhece se um rosto está ou não portando uma máscara! O código utiliza da bib
Graphing communities on Twitch.tv in a visually intuitive way
VisualizingTwitchCommunities This project maps communities of streamers on Twitch.tv based on shared viewership. The data is collected from the Twitch
Big Bird: Transformers for Longer Sequences
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
Converts Betaflight blackbox gyro to MP4 GoPro Meta data so it can be used with ReelSteady GO
Here are a bunch of scripts that I created some time ago as a proof of concept that Betaflight blackbox gyro data can be converted to GoPro Metadata F
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS)
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS) Yoonhyung Lee, Joongbo Shin, Kyomin Jung Abstract: Although early
AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints
AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints Reward Function Template for waypoints def reward_function(params):
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt.
UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive
Learning to Simulate Dynamic Environments with GameGAN (CVPR 2020)
Learning to Simulate Dynamic Environments with GameGAN PyTorch code for GameGAN Learning to Simulate Dynamic Environments with GameGAN Seung Wook Kim,
Explainability for Vision Transformers (in PyTorch)
Explainability for Vision Transformers (in PyTorch) This repository implements methods for explainability in Vision Transformers
Export your data from Xiami
Xiami Exporter 导出虾米音乐的个人数据,功能: 导出歌曲为 json 收藏歌曲 收藏专辑 播放列表 导出收藏艺人为 json 导出收藏专辑为 json 导出播放列表为 json (个人和收藏) 将导出的数据整理至 sqlite 数据库 收藏歌曲 收藏艺人 收藏专辑 播放列表 下载已导出
Code for the paper Learning the Predictability of the Future
Learning the Predictability of the Future Code from the paper Learning the Predictability of the Future. Website of the project in hyperfuture.cs.colu
State of the Art Neural Networks for Deep Learning
pyradox This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2
PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing
PhoNLP is a multi-task learning model for joint part-of-speech (POS) tagging, named entity recognition (NER) and dependency parsing. Experiments on Vietnamese benchmark datasets show that PhoNLP produces state-of-the-art results, outperforming a single-task learning approach that fine-tunes the pre-trained Vietnamese language model PhoBERT for each task independently.
Official TensorFlow code for the forthcoming paper
~ Efficient-CapsNet ~ Are you tired of over inflated and overused convolutional neural networks? You're right! It's time for CAPSULES :)
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Performant, differentiable reinforcement learning
deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo
An open framework for Federated Learning.
Welcome to Intel® Open Federated Learning Federated learning is a distributed machine learning approach that enables organizations to collaborate on m
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi
An API serving data on all creatures, monsters, materials, equipment, and treasure in The Legend of Zelda: Breath of the Wild
Hyrule Compendium API An API serving data on all creatures, monsters, materials, equipment, and treasure in The Legend of Zelda: Breath of the Wild. B
Implementation of Supervised Contrastive Learning with AMP, EMA, SWA, and many other tricks
SupCon-Framework The repo is an implementation of Supervised Contrastive Learning. It's based on another implementation, but with several differencies
Sample code from the Neural Networks from Scratch book.
Neural Networks from Scratch (NNFS) book code Code from the NNFS book (https://nnfs.io) separated by chapter.
Code for "Layered Neural Rendering for Retiming People in Video."
Layered Neural Rendering in PyTorch This repository contains training code for the examples in the SIGGRAPH Asia 2020 paper "Layered Neural Rendering
Age and Gender prediction using Keras
cnn_age_gender Age and Gender prediction using Keras Dataset example : Description : UTKFace dataset is a large-scale face dataset with long age span
Neural Magic Eye: Learning to See and Understand the Scene Behind an Autostereogram, arXiv:2012.15692.
Neural Magic Eye Preprint | Project Page | Colab Runtime Official PyTorch implementation of the preprint paper "NeuralMagicEye: Learning to See and Un
Soda SQL Data testing, monitoring and profiling for SQL accessible data.
Soda SQL Data testing, monitoring and profiling for SQL accessible data. What does Soda SQL do? Soda SQL allows you to Stop your pipeline when bad dat
Client library to download and publish models and other files on the huggingface.co hub
huggingface_hub Client library to download and publish models and other files on the huggingface.co hub Do you have an open source ML library? We're l
[AAAI 21] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning
◥ Curriculum Labeling ◣ Revisiting Pseudo-Labeling for Semi-Supervised Learning Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez. In the
This repository contains code examples and documentation for learning how applications can be developed with Kubernetes
BigBitBus KAT Components Click on the diagram to enlarge, or follow this link for detailed documentation Introduction Welcome to the BigBitBus Kuberne
A framework for joint super-resolution and image synthesis, without requiring real training data
SynthSR This repository contains code to train a Convolutional Neural Network (CNN) for Super-resolution (SR), or joint SR and data synthesis. The met
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"
C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/
A PyTorch re-implementation of the paper 'Exploring Simple Siamese Representation Learning'. Reproduced the 67.8% Top1 Acc on ImageNet.
Exploring simple siamese representation learning This is a PyTorch re-implementation of the SimSiam paper on ImageNet dataset. The results match that
This repository is related to an Arabic tutorial, within the tutorial we discuss the common data structure and algorithms and their worst and best case for each, then implement the code using Python.
Data Structure and Algorithms with Python This repository is related to the Arabic tutorial here, within the tutorial we discuss the common data struc
FLEX (Federated Learning EXchange,FLEX) protocol is a set of standardized federal learning agreements designed by Tongdun AI Research Group。
Click to view Chinese version FLEX (Federated Learning Exchange) protocol is a set of standardized federal learning agreements designed by Tongdun AI
Transformers are Graph Neural Networks!
🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article
The fastest way to visualize GradCAM with your Keras models.
VizGradCAM VizGradCam is the fastest way to visualize GradCAM in Keras models. GradCAM helps with providing visual explainability of trained models an
:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)
R²SQL The PyTorch implementation of paper Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing. (AAAI 2021) Requirement
A Pythonic client for the official https://data.gov.gr API.
pydatagovgr An unofficial Pythonic client for the official data.gov.gr API. Aims to be an easy, intuitive and out-of-the-box way to: find data publish
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
CyGNet This repository reproduces the AAAI'21 paper “Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Network
FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX.
FedJAX: Federated learning with JAX What is FedJAX? FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX. FedJAX priori
An end-to-end machine learning web app to predict rugby scores (Pandas, SQLite, Keras, Flask, Docker)
Rugby score prediction An end-to-end machine learning web app to predict rugby scores Overview An demo project to provide a high-level overview of the
Spectrum is an AI that uses machine learning to generate Rap song lyrics
Spectrum Spectrum is an AI that uses deep learning to generate rap song lyrics. View Demo Report Bug Request Feature Open In Colab About The Project S
Graph neural network message passing reframed as a Transformer with local attention
Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with
Official PyTorch implementation for paper Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra
Official implementation of AAAI-21 paper "Label Confusion Learning to Enhance Text Classification Models"
Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str
Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021
Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom
Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166
Region Proportion Regularized Inference (RePRI) for Few-Shot Segmentation In this repo, we provide the code for our paper : "Few-Shot Segmentation Wit
An open source robotics benchmark for meta- and multi-task reinforcement learning
Meta-World Meta-World is an open-source simulated benchmark for meta-reinforcement learning and multi-task learning consisting of 50 distinct robotic
A toolkit for reproducible reinforcement learning research.
garage garage is a toolkit for developing and evaluating reinforcement learning algorithms, and an accompanying library of state-of-the-art implementa
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us
Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
SLM Lab Modular Deep Reinforcement Learning framework in PyTorch. Documentation: https://slm-lab.gitbook.io/slm-lab/ BeamRider Breakout KungFuMaster M
Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information. :godmode:
ViZDoom ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
Serpent.AI - Game Agent Framework (Python) Update: Revival (May 2020) Development work has resumed on the framework with the aim of bringing it into 2
A toolkit for developing and comparing reinforcement learning algorithms.
Status: Maintenance (expect bug fixes and minor updates) OpenAI Gym OpenAI Gym is a toolkit for developing and comparing reinforcement learning algori
A customisable 3D platform for agent-based AI research
DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a
A minimalistic library designed to provide native access to YNAB data from Python
pYNAB A minimalistic library designed to provide native access to YNAB data from Python. Install The simplest way is to install the latest version fro
Tesseract Open Source OCR Engine (main repository)
Tesseract OCR About This package contains an OCR engine - libtesseract and a command line program - tesseract. Tesseract 4 adds a new neural net (LSTM
Python wrapper for the Sportradar APIs ⚽️🏈
Sportradar APIs This is a Python wrapper for the sports APIs provided by Sportradar. You'll need to sign up for an API key to use the service. Sportra
Python client for the Socrata Open Data API
sodapy sodapy is a python client for the Socrata Open Data API. Installation You can install with pip install sodapy. If you want to install from sour
Official Python client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Python apps.
MonkeyLearn API for Python Official Python client for the MonkeyLearn API. Build and run machine learning models for language processing from your Pyt
A Python API to retrieve and read MLB GameDay data
mlbgame mlbgame is a Python API to retrieve and read MLB GameDay data. mlbgame works with real time data, getting information as games are being playe
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 tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
:snake: A simple library to fetch data from the iTunes Store API made for Python = 3.5
itunespy itunespy is a simple library to fetch data from the iTunes Store API made for Python 3.5 and beyond. Important: Since version 1.6 itunespy no
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. 150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
Stock Analysis Engine Build and tune investment algorithms for use with artificial intelligence (deep neural networks) with a distributed stack for ru
Python SDK for IEX Cloud
iexfinance Python SDK for IEX Cloud. Architecture mirrors that of the IEX Cloud API (and its documentation). An easy-to-use toolkit to obtain data for
Python bindings for BigML.io
BigML Python Bindings BigML makes machine learning easy by taking care of the details required to add data-driven decisions and predictive power to yo
Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.
Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes
Faker is a Python package that generates fake data for you.
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in yo
create custom test databases that are populated with fake data
About Generate fake but valid data filled databases for test purposes using most popular patterns(AFAIK). Current support is sqlite, mysql, postgresql
Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.
Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes
Faker is a Python package that generates fake data for you.
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in yo
create custom test databases that are populated with fake data
About Generate fake but valid data filled databases for test purposes using most popular patterns(AFAIK). Current support is sqlite, mysql, postgresql
Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files
pyexcel - Let you focus on data, instead of file formats Support the project If your company has embedded pyexcel and its components into a revenue ge
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
A TensorFlow recommendation algorithm and framework in Python.
TensorRec A TensorFlow recommendation algorithm and framework in Python. NOTE: TensorRec is not under active development TensorRec will not be receivi
Deep recommender models using PyTorch.
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin
A Python implementation of LightFM, a hybrid recommendation algorithm.
LightFM Build status Linux OSX (OpenMP disabled) Windows (OpenMP disabled) LightFM is a Python implementation of a number of popular recommendation al
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Implicit Fast Python Collaborative Filtering for Implicit Datasets. This project provides fast Python implementations of several different popular rec
fastFM: A Library for Factorization Machines
Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat