3309 Repositories
Python bayesian-data-analysis Libraries
[CVPR 2021 Oral] ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis
ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis [arxiv|pdf|v
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.
Diffgram - Supervised Learning Data Platform
Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning
addon for blender to import mocap data from tools like easymocap, frankmocap and Vibe
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.
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.
📼Command line tool based on youtube-dl to easily download selected channels from your subscriptions.
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
Policy and data administration, distribution, and real-time updates on top of Open Policy Agent
⚡ OPAL ⚡ Open Policy Administration Layer OPAL is an administration layer for Open Policy Agent (OPA), detecting changes to both policy and policy dat
Visualize classified time series data with interactive Sankey plots in Google Earth Engine
sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P
Code related to "Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity" paper
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
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for
A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
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
DABO: Data Augmentation with Bilevel Optimization [Paper] The goal is to automatically learn an efficient data augmentation regime for image classific
AutoOED: Automated Optimal Experiment Design Platform
AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems and automatically guides the design of experiment to be evaluated.
Wetterdienst - Open weather data for humans
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.
TTS is a library for advanced Text-to-Speech generation.
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. TTS comes with pretrained models, tools for measuring dataset quality and already used in 20+ languages for products and research projects.
Data Visualization Guide for Presentations, Reports, and Dashboards
This is a highly practical and example-based guide on visually representing data in reports and dashboards.
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning Warning: This is a rapidly evolving research prototype.
Domain Connectivity Analysis Tools to analyze aggregate connectivity patterns across a set of domains during security investigations
DomainCAT (Domain Connectivity Analysis Tool) Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of dom
Newt - a Gaussian process library in JAX.
Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\
Py-FEAT: Python Facial Expression Analysis Toolbox
Py-FEAT is a suite for facial expressions (FEX) research written in Python. This package includes tools to detect faces, extract emotional facial expressions (e.g., happiness, sadness, anger), facial muscle movements (e.g., action units), and facial landmarks, from videos and images of faces, as well as methods to preprocess, analyze, and visualize FEX data.
POT : Python Optimal Transport
This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s
Algorithmic trading using machine learning.
Algorithmic Trading This machine learning algorithm was built using Python 3 and scikit-learn with a Decision Tree Classifier. The program gathers sto
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi
Using python and scikit-learn to make stock predictions
MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni
Python Data. Leaflet.js Maps.
folium Python Data, Leaflet.js Maps folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js
High-level geospatial data visualization library for Python.
geoplot: geospatial data visualization geoplot is a high-level Python geospatial plotting library. It's an extension to cartopy and matplotlib which m
Satellite imagery for dummies.
felicette Satellite imagery for dummies. What can you do with this tool? TL;DR: Generate JPEG earth imagery from coordinates/location name with public
Raster-based Spatial Analysis for Python
🌍 xarray-spatial: Raster-Based Spatial Analysis in Python 📍 Fast, Accurate Python library for Raster Operations ⚡ Extensible with Numba ⏩ Scalable w
Blender addons to make the bridge between Blender and geographic data
Blender GIS Blender minimal version : 2.8 Mac users warning : currently the addon does not work on Mac with Blender 2.80 to 2.82. Please do not report
Implementation of Trajectory classes and functions built on top of GeoPandas
MovingPandas MovingPandas implements a Trajectory class and corresponding methods based on GeoPandas. Visit movingpandas.org for details! You can run
A Python package for delineating nested surface depressions from digital elevation data.
Welcome to the lidar package lidar is Python package for delineating the nested hierarchy of surface depressions in digital elevation models (DEMs). I
A toolbox for processing earth observation data with Python.
eo-box eobox is a Python package with a small collection of tools for working with Remote Sensing / Earth Observation data. Package Overview So far, t
scalable analysis of images and time series
thunder scalable analysis of image and time series analysis in python Thunder is an ecosystem of tools for the analysis of image and time series data
framework for large-scale SAR satellite data processing
pyroSAR A Python Framework for Large-Scale SAR Satellite Data Processing The pyroSAR package aims at providing a complete solution for the scalable or
Automated download of LANDSAT data from USGS website
LANDSAT-Download It seems USGS has changed the structure of its data, and so far, I have not been able to find the direct links to the products? Help
gpdvega is a bridge between GeoPandas and Altair that allows to seamlessly chart geospatial data
gpdvega gpdvega is a bridge between GeoPandas a geospatial extension of Pandas and the declarative statistical visualization library Altair, which all
Processing and interpolating spatial data with a twist of machine learning
Documentation | Documentation (dev version) | Contact | Part of the Fatiando a Terra project About Verde is a Python library for processing spatial da
peartree: A library for converting transit data into a directed graph for sketch network analysis.
peartree 🍐 🌳 peartree is a library for converting GTFS feed schedules into a representative directed network graph. The tool uses Partridge to conve
Tools for the extraction of OpenStreetMap street network data
OSMnet Tools for the extraction of OpenStreetMap (OSM) street network data. Intended to be used in tandem with Pandana and UrbanAccess libraries to ex
Open GeoJSON data on geojson.io
geojsonio.py Open GeoJSON data on geojson.io from Python. geojsonio.py also contains a command line utility that is a Python port of geojsonio-cli. Us
Tool to suck data from ArcGIS Server and spit it into PostgreSQL
chupaESRI About ChupaESRI is a Python module/command line tool to extract features from ArcGIS Server map services. Name? Think "chupacabra" or "Chupa
Pandas Network Analysis: fast accessibility metrics and shortest paths, using contraction hierarchies :world_map:
Pandana Pandana is a Python library for network analysis that uses contraction hierarchies to calculate super-fast travel accessibility metrics and sh
OSMnx: Python for street networks. Retrieve, model, analyze, and visualize street networks and other spatial data from OpenStreetMap.
OSMnx OSMnx is a Python package that lets you download geospatial data from OpenStreetMap and model, project, visualize, and analyze real-world street
PyTorch implementation of the Deep SLDA method from our CVPRW-2020 paper "Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis"
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis This is a PyTorch implementation of the Deep Streaming Linear Discriminant
This python module can analyse cryptocurrency news for any number of coins given and return a sentiment. Can be easily integrated with a Trading bot to keep an eye on the news.
Python script that analyses news headline or body sentiment and returns the overall media sentiment of any given coin. It can take multiple coins an
Layout Parser is a deep learning based tool for document image layout analysis tasks.
A Python Library for Document Layout Understanding
Apache Superset is a Data Visualization and Data Exploration Platform
Apache Superset is a Data Visualization and Data Exploration Platform
Distribution Analyser is a Web App that allows you to interactively explore continuous distributions from SciPy and fit distribution(s) to your data.
Distribution Analyser Distribution Analyser is a Web App that allows you to interactively explore continuous distributions from SciPy and fit distribu
Hands-on machine learning workshop
emb-ntua-workshop This workshop discusses introductory concepts of machine learning and data mining following a hands-on approach using popular tools
原神抽卡记录数据集-Genshin Impact gacha data
提要 持续收集原神抽卡记录中 可以使用抽卡记录导出工具导出抽卡记录的json,将json文件发送至[email protected],我会在清除个人信息后将文件提交到此处。以下两种导出工具任选其一即可。 一种抽卡记录导出工具 from sunfkny 使用方法演示视频 另一种electron版的抽
The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".
Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in
Code, Data and Demo for Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting
InversePrompting Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting Code: The code is provided in the "chinese_ip"
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language This repository contains UA-GEC data and an accompanying Python lib
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Demo video: CVPR 2021 Oral: Single Channel Manipulation: Localized or attribu
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
Semi-supervised Learning for Sentiment Analysis
Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo
An open-source library of algorithms to analyse time series in GPU and CPU.
An open-source library of algorithms to analyse time series in GPU and CPU.
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)
wsss-analysis The code of: A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains, arXiv pre-print 2019 paper.
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
Ingest openldap data into bloodhound
Bloodhound for Linux Ingest a dumped OpenLDAP ldif into neo4j to be visualized in Bloodhound. Usage: ./ldif_to_neo4j.py ./sample.ldif | cypher-shell -
Using Hotel Data to predict High Value And Potential VIP Guests
Description Using hotel data and AI to predict high value guests and potential VIP guests. Hotel can leverage on prediction resutls to run more effect
Flenser is a simple, minimal, automated exploratory data analysis tool.
Flenser Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs
Data Orchestration Platform
Table of contents What is DOP Design Concept A Typical DOP Orchestration Flow Prerequisites - Run in Docker For DOP Native Features For DBT Instructio
The most widely used Python to C compiler
Welcome to Cython! Cython is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports mo
IPython: Productive Interactive Computing
IPython: Productive Interactive Computing Overview Welcome to IPython. Our full documentation is available on ipython.readthedocs.io and contains info
Socorro is the Mozilla crash ingestion pipeline. It accepts and processes Breakpad-style crash reports. It provides analysis tools.
Socorro Socorro is a Mozilla-centric ingestion pipeline and analysis tools for crash reports using the Breakpad libraries. Support This is a Mozilla-s
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
Boltons boltons should be builtins. Boltons is a set of over 230 BSD-licensed, pure-Python utilities in the same spirit as — and yet conspicuously mis
Viewflow is an Airflow-based framework that allows data scientists to create data models without writing Airflow code.
Viewflow Viewflow is a framework built on the top of Airflow that enables data scientists to create materialized views. It allows data scientists to f
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning
The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and
Statistical package in Python based on Pandas
Pingouin is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. F
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis
Using approximate bayesian posteriors in deep nets for active learning
Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
pyhsmm MITpyhsmm - Bayesian inference in HSMMs and HMMs. MIT
Bayesian inference in HSMMs and HMMs This is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and expli
BAyesian Model-Building Interface (Bambi) in Python.
Bambi BAyesian Model-Building Interface in Python Overview Bambi is a high-level Bayesian model-building interface written in Python. It's built on to
Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris, Fractional Factorial and FAST methods.
Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Gaussian processes in TensorFlow
Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl
Data Analysis Baseline Library
dabl The data analysis baseline library. "Mr Sanchez, are you a data scientist?" "I dabl, Mr president." Find more information on the website. State o
Topological Data Analysis for Python🐍
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
scikit-learn cross validators for iterative stratification of multilabel data
iterative-stratification iterative-stratification is a project that provides scikit-learn compatible cross validators with stratification for multilab
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License
A library of extension and helper modules for Python's data analysis and machine learning libraries.
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
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla
A simplified framework and utilities for PyTorch
Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench
Library for faster pinned CPU - GPU transfer in Pytorch
SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases.
Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl