3312 Repositories
Python time-series-data-mining Libraries
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
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
Get Landsat surface reflectance time-series from google earth engine
geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On
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
Yet Another Time Series Model
Yet Another Timeseries Model (YATSM) master v0.6.x-maintenance Build Coverage Docs DOI | About Yet Another Timeseries Model (YATSM) is a Python packag
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
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
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea
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
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
Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral
NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video Project Page | Paper NeuralRecon: Real-Time Coherent 3D Reconstruction from Mon
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 -
Examples and code for the Practical Machine Learning workshop series
Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D
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
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr
🔩 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
Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in
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
The (Python-based) mining software required for the Game Boy mining project.
ntgbtminer - Game Boy edition This is a version of ntgbtminer that works with the Game Boy bitcoin miner. ntgbtminer ntgbtminer is a no thrills getblo
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 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
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
PyTorch extensions for fast R&D prototyping and Kaggle farming
Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What
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
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
A lightweight, GPU accelerated, SQL engine built on the RAPIDS.ai ecosystem. Get Started on app.blazingsql.com Getting Started | Documentation | Examp
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi
Distributed scikit-learn meta-estimators in PySpark
sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin
BigDL: Distributed Deep Learning Framework for Apache Spark
BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w
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.
Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear
A python library for Bayesian time series modeling
PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W
AtsPy: Automated Time Series Models in Python (by @firmai)
Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp
A Python toolkit for rule-based/unsupervised anomaly detection in time series
Anomaly Detection Toolkit (ADTK) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.
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
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile
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
Python module for machine learning time series:
seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr
Time series forecasting with PyTorch
Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time
A Python package for time series classification
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 is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks
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
A python library for easy manipulation and forecasting of time series.
Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from
Probabilistic time series modeling in Python
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
Real-time stream processing for python
Streamz Streamz helps you build pipelines to manage continuous streams of data. It is simple to use in simple cases, but also supports complex pipelin
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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
A unified framework for machine learning with time series
Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible
Automatic extraction of relevant features from time series:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
ARCH models in Python
arch Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python (with Cython and/or Numba used
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technol
Technical Analysis Library using Pandas and Numpy
Technical Analysis Library in Python It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Cl
A python wrapper for Alpha Vantage API for financial data.
alpha_vantage Python module to get stock data/cryptocurrencies from the Alpha Vantage API Alpha Vantage delivers a free API for real time financial da
Yahoo! Finance market data downloader (+faster Pandas Datareader)
Yahoo! Finance market data downloader Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop work
python toolbox for visualizing geographical data and making maps
geoplotlib is a python toolbox for visualizing geographical data and making maps data = read_csv('data/bus.csv') geoplotlib.dot(data) geoplotlib.show(
Use Mapbox GL JS to visualize data in a Python Jupyter notebook
Location Data Visualization library for Jupyter Notebooks Library documentation at https://mapbox-mapboxgl-jupyter.readthedocs-hosted.com/en/latest/.
Search and download Copernicus Sentinel satellite images
sentinelsat Sentinelsat makes searching, downloading and retrieving the metadata of Sentinel satellite images from the Copernicus Open Access Hub easy
Python package for earth-observing satellite data processing
Satpy The Satpy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data f
A package built to support working with spatial data using open source python
EarthPy EarthPy makes it easier to plot and manipulate spatial data in Python. Why EarthPy? Python is a generic programming language designed to suppo
Documentation and samples for ArcGIS API for Python
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
Fiona reads and writes geographic data files
Fiona Fiona reads and writes geographic data files and thereby helps Python programmers integrate geographic information systems with other computer s
Python tools for geographic data
GeoPandas Python tools for geographic data Introduction GeoPandas is a project to add support for geographic data to pandas objects. It currently impl
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
WebGL2 powered geospatial visualization layers
deck.gl | Website WebGL2-powered, highly performant large-scale data visualization deck.gl is designed to simplify high-performance, WebGL-based visua
Apache Flink
Apache Flink Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities. Learn more about Flin
Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous Event-Based Data"
A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous
2D Time independent Schrodinger equation solver for arbitrary shape of well
Schrodinger Well Python Python solver for timeless Schrodinger equation for well with arbitrary shape https://imgur.com/a/jlhK7OZ Pictures of circular
An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.
SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow