Python Graph-data-augmentation Resources

When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi

Expressive Power of Invariant and Equivaraint Graph Neural Networks In this repository, we show how to use powerful GNN (2-FGNN) to solve a graph alig

Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.

⚛️ Clonebot - Heroku version ⚡ CloneBot is a telegram bot that allows you to copy folder/team drive to team drives. One of the main advantage of this

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod

Public Datasets Pipelines Cloud-native, data pipeline architecture for onboarding datasets to the Google Cloud Public Datasets Program. Overview Requi

GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai

AWS Data Engineering Pipeline This is a repository for the Duke University Cloud Computing course project on Serverless Data Engineering Pipeline. For

Tamil Nadu Chief Minister's Relief Fund Donors Scrapped data from https://ereceipt.tn.gov.in/cmprf/Interface/CMPRF/MonthWiseReport Scrapper scrapper.p

iterable-subprocess Python utility function to communicate with a subprocess using iterables: for when data is too big to fit in memory and has to be

Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio

A package to aggregate gridded data in xarray to polygons in geopandas using area-weighting from the relative area overlaps between pixels and polygons.

Graphsignal Logger Overview Graphsignal is an observability platform for monitoring and troubleshooting production machine learning applications. It h

Python function to stream unzip all the files in a ZIP archive: without loading the entire ZIP file or any of its files into memory at once

Show Data is to generate html tables for large scale image dataset, especially for the dataset in remote server. It provides some useful commond line tools and fully customizeble API reference to generate html table different tasks.

Stream Framework Activity Streams & Newsfeeds Stream Framework is a Python library which allows you to build activity streams & newsfeeds using Cassan

tinkproject The program for portfolio analysis via Tinkoff API Hello! This is my first project, please, don't judge me. This project was developed for

Multi-Task Framework for Cross-Lingual Abstractive Summarization (MCLAS) The code for ACL2021 paper Cross-Lingual Abstractive Summarization with Limit

A curated list of programmatic weak supervision papers and resources

Deep learning toolbox based on PyTorch for hyperspectral data classification.

Code & Data for Enhancing Photorealism Enhancement

A framework for cleaning Chinese dialog data

Esparto is a simple HTML and PDF document generator for Python. Its primary use is for generating shareable single page reports with content from popular analytics and data science libraries.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

👩‍✈️ Coqpit Simple, light-weight and no dependency config handling through python data classes with to/from JSON serialization/deserialization. Curre

PairRE Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors. This implementation of PairRE for Open Graph Benchmak datasets (

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation This repository contains the official implementation of our paper: Self-su

This is the XLM-T repository, which includes data, code and pre-trained multilingual language models for Twitter. XLM-T - A Multilingual Language Mode

Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.

Hue Editor: Open source SQL Query Assistant for Databases/Warehouses

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar

torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions.

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

erdantic is a simple tool for drawing entity relationship diagrams (ERDs) for Python data model classes. Diagrams are rendered using the venerable Graphviz library.

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data [WIP] Unofficial Pytorch implementation of AdaSpeech 2. Requirements : All code written i

CLEAR: Consistent Lifting, Embedding, and Alignment Rectification Algorithm The Matlab, Python, and C++ implementation of the CLEAR algorithm, as desc

Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay

LADA This repo contains codes for the following paper: Jiaao Chen*, Zhenghui Wang*, Ran Tian, Zichao Yang, Diyi Yang: Local Additivity Based Data Augm

Learning Representational Invariances for Data-Efficient Action Recognition Official PyTorch implementation for Learning Representational Invariances

django-import-export django-import-export is a Django application and library for importing and exporting data with included admin integration. Featur

Desmos Bezier Renderer A simple image/video to Desmos graph converter run locally Sample Result Setup Install dependencies apt update apt install git

causaldata This repository will contain R, Stata, and Python packages, all called causaldata, which contain data sets that can be used to implement th

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

hyppo (HYPothesis Testing in PythOn, pronounced "Hippo") is an open-source software package for multivariate hypothesis testing.

Algo Drills A command line tool for memorizing algorithms in Python by typing them. In alpha and things will change. How it works Type out an algorith

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

SharinGAN Official repo for the work titled "SharinGAN: Combining Synthetic and Real Data for Unsupervised GeometryEstimation" The official project we

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

pihole-antitelemetry Research shows Google collects 20x more data from Android than Apple collects from iOS. Block both using these pihole lists. Proj

SARS-CoV-2 processing requests Request execution of Galaxy SARS-CoV-2 variation analysis workflows on input data you provide. Prerequisites This autom

FastAPI-Wrapper CLI & APIness Streamlit App Arvindra Sehmi, Oxford Economics Ltd. | Website | LinkedIn (Updated: 21 April, 2021) fastapi-wrapper is mo

xarray-sentinel WARNING: this product is a "technology preview" / pre-Alpha Xarray backend to explore and load Copernicus Sentinel-1 satellite data pr

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

Introduction This is the PyTorch implementation for Adaptive Graph Representation Learning for Video Person Re-identification. Get started git clone h

Fine-Grained R2R Code and data of the Fine-Grained R2R Dataset proposed in the EMNLP2020 paper Sub-Instruction Aware Vision-and-Language Navigation. C

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.

🏅 Collection of Kaggle Solutions and Ideas 🏅

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

small python skript to display tradegate data on a waveshare e-ink important you need locale "de_AT.UTF-8 UTF-8" installed. do so in raspi-config's Lo

This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).

SpikeX is a collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction tools with almost-zero effort.

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Knowledge Graph,Question Answering System，基于知识图谱和向量检索的医疗诊断问答系统

Dice Loss for NLP Tasks This repository contains code for Dice Loss for Data-imbalanced NLP Tasks at ACL2020. Setup Install Package Dependencies The c

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels without pre-existing datasets. The only available option is often to collect and annotate texts by hand, which is expensive and time-consuming.

drawdata This small python app allows you to draw a dataset in a jupyter notebook. This should be very useful when teaching machine learning algorithm

ETL Pipeline with Airflow, Spark, s3, MongoDB and Amazon Redshift

libmaths libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat

Compact Transformers Preprint Link: Escaping the Big Data Paradigm with Compact Transformers By Ali Hassani[1]*, Steven Walton[1]*, Nikhil Shah[1], Ab

Simple but maybe too simple config management through python data classes. We use it for machine learning.

README Augment training images for deep neural networks by randomizing their visual style, as described in our paper: https://arxiv.org/abs/1809.05375

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation The code of: Context Decoupling Augmentation for Weakly Supervised Semanti

b3d_mocap_import addon for blender to import mocap data from tools like easymocap, frankmocap and Vibe ==================VIBE================== To use

The Django Leaflet Admin List package provides an admin list view featured by the map and bounding box filter for the geo-based data of the GeoDjango. It requires a django-leaflet package.

youtube-cdl Command line tool based on youtube-dl to easily download selected channels from your subscriptions. This tool is very handy if you want to

⚡ OPAL ⚡ Open Policy Administration Layer OPAL is an administration layer for Open Policy Agent (OPA), detecting changes to both policy and policy dat

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

DataTuner You have just found the DataTuner. This repository provides tools for fine-tuning language models for a task. See LICENSE.txt for license de

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

DABO: Data Augmentation with Bilevel Optimization [Paper] The goal is to automatically learn an efficient data augmentation regime for image classific

QA-GNN: Question Answering using Language Models and Knowledge Graphs This repo provides the source code & data of our paper: QA-GNN: Reasoning with L

We are a group of like-minded people trying to make access to weather data in Python feel like a warm summer breeze, similar to other projects like rdwd for the R language, which originally drew our interest in this project.