Python Graph-analysis Resources

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

Scikit-TDA is a home for Topological Data Analysis Python libraries intended for non-topologists. This project aims to provide a curated library of TD

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

cuGraph - GPU Graph Analytics The RAPIDS cuGraph library is a collection of GPU accelerated graph algorithms that process data found in GPU DataFrames

Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp

Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp

matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo

pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

Surpriver - Find High Moving Stocks before they Move Find high moving stocks before they move using anomaly detection and machine learning. Surpriver

FinTA (Financial Technical Analysis) Common financial technical indicators implemented in Pandas. This is work in progress, bugs are expected and resu

CryptoSignal - #1 Quant Trading & Technical Analysis Bot - 2,100 + stars, 580 + forks https://github.com/CryptoSignal/Crypto-Signal Development state:

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

Technical Analysis Library in Python It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Cl

Python Spatial Analysis Library PySAL, the Python spatial analysis library, is an open source cross-platform library for geospatial data science with

ArcGIS API for Python ArcGIS API for Python is a Python library for working with maps and geospatial data, powered by web GIS. It provides simple and

Shapely Manipulation and analysis of geometric objects in the Cartesian plane. Shapely is a BSD-licensed Python package for manipulation and analysis

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B

QC-DGM This is the official PyTorch implementation and models for our CVPR 2021 paper: Deep Graph Matching under Quadratic Constraint. It also contain

Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R

ID Verification by LibraX.ai This is the first free Identity verification in the market. LibraX.ai is an identity verification platform for developers

Open Semantic Search https://opensemanticsearch.org Integrated search server, ETL framework for document processing (crawling, text extraction, text a

ocropy OCRopus is a collection of document analysis programs, not a turn-key OCR system. In order to apply it to your documents, you may need to do so

SCUT-CTW1500 Datasets We have updated annotations for both train and test set. Train: 1000 images [images][annos] Additional point annotation for each

Eynollah Document Layout Analysis Introduction This tool performs document layout analysis (segmentation) from image data and returns the results as P

OCR Segmentation a deep learning model for page layout analysis / segmentation. dependencies tensorflow1.8 python3 dataset: uw3-framed-lines-degraded-

LayoutAnalysisEvaluator Layout Analysis Evaluator for: ICDAR 2019 Historical Document Reading Challenge on Large Structured Chinese Family Records ICD

ocroseg This is a deep learning model for page layout analysis / segmentation. There are many different ways in which you can train and run it, but by

P2PaLA Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks. 💥 Try our new DEMO for online baseli

Run the application: python main.py *Note: For first time running the application, create a folder named "output". The application is a simple documen

Layout_Analysis Introduction This is an implementation of RLSA and X-Y Cut with OpenCV Dependencies OpenCV 3.0+ How to use Compile with g++ : g++ -std

Deep Learning Based Page Layout Analyze This is a Python implementaion of page layout analyze tool. The goal of page layout analyze is to segment page

LAREX LAREX is a semi-automatic open-source tool for layout analysis on early printed books. It uses a rule based connected components approach which

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

Kalman Filter in Python This is a basic example of how Kalman filter works in Python. I do plan on refactoring and expanding this repo in the future.

Negative Sampling for NER Unlabeled entity problem is prevalent in many NER scenarios (e.g., weakly supervised NER). Our paper in ICLR-2021 proposes u

DeepSphere-Weather - Deep Learning on the sphere for weather/climate applications. The code in this repository provides a scalable and flexible framew

IIM - Crowd Localization This repo is the official implementation of paper: Learning Independent Instance Maps for Crowd Localization. The code is dev

Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We

TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c

Learning Intents behind Interactions with Knowledge Graph for Recommendation This is our PyTorch implementation for the paper: Xiang Wang, Tinglin Hua

SpiderFoot is an open source intelligence (OSINT) automation tool. It integrates with just about every data source available and utilises a range of m

Cowrie Welcome to the Cowrie GitHub repository This is the official repository for the Cowrie SSH and Telnet Honeypot effort. What is Cowrie Cowrie is

Trafalgar Python library to make development of portfolio analysis faster and easier Installation 🔥 For the moment, Trafalgar is still in beta develo

tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f

SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor

sentello Sentello is a python script that simulates the anti-evasion and anti-analysis techniques used by malware. For techniques that are difficult t

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

pandas_summary An extension to pandas dataframes describe function. The module contains DataFrameSummary object that extend describe() with: propertie

madmom Madmom is an audio signal processing library written in Python with a strong focus on music information retrieval (MIR) tasks. The library is i

Welcome to MARSYAS. MARSYAS is a software framework for rapid prototyping of audio applications, with flexibility and extensibility as primary concer

Essentia Essentia is an open-source C++ library for audio analysis and audio-based music information retrieval released under the Affero GPL license.

aubio aubio is a library to label music and sounds. It listens to audio signals and attempts to detect events. For instance, when a drum is hit, at wh

POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa

emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

dovpanda Directions OVer PANDAs Directions are hints and tips for using pandas in an analysis environment. dovpanda is an overlay companion for workin

datatable This is a Python package for manipulating 2-dimensional tabular data structures (aka data frames). It is close in spirit to pandas or SFrame

XPandas (extended Pandas) implements 1D and 2D data containers for storing type-heterogeneous tabular data of any type, and encapsulates feature extra

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

TensorFlow Model Analysis TensorFlow Model Analysis (TFMA) is a library for evaluating TensorFlow models. It allows users to evaluate their models on

Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual

Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to

Documentation | Paper | Colab Notebooks | External Resources | OGB Examples PyTorch Geometric (PyG) is a geometric deep learning extension library for

imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour

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

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This

E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G

Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program

Table of contents What is PEM? Overview Installation Usage Executable Library Telegram Bot Try OPEM in Your Browser! MATLAB Issues & Bug Reports Contr

MOSAIC: A modular single-molecule analysis interface MOSAIC is a single molecule analysis toolbox that automatically decodes multi-state nanopore data

CellProfiler is a free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure

Friture Friture is an application to visualize and analyze live audio data in real-time. Friture displays audio data in several widgets, such as a sco

Easy to setup customizable honeypots for monitoring network traffic, bots activities and username\password credentials. The current available honeypot

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

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

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

Photonix Photo Manager This is a photo management application based on web technologies. Run it on your home server and it will let you find what you

ocropy OCRopus is a collection of document analysis programs, not a turn-key OCR system. In order to apply it to your documents, you may need to do so

a BTC Clipper or a "Bitcoin Clipper" is a type of malware designed to target cryptocurrency transactions.

Notion Graph View Export Notion pages to a Roam Research like graph view.

A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind

BaseSpec is a system that performs a comparative analysis of baseband implementation and the specifications of cellular networks. The key intuition of BaseSpec is that a message decoder in baseband software embeds the protocol specification in a machine-friendly structure to parse incoming messages;

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.

This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.

xgbse: XGBoost Survival Embeddings "There are two cultures in the use of statistical modeling to reach conclusions from data