Python Data-Analysis-Report Resources

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.

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

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.

Bloodhound for Linux Ingest a dumped OpenLDAP ldif into neo4j to be visualized in Bloodhound. Usage: ./ldif_to_neo4j.py ./sample.ldif | cypher-shell -

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 Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs

Table of contents What is DOP Design Concept A Typical DOP Orchestration Flow Prerequisites - Run in Docker For DOP Native Features For DBT Instructio

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 Overview Welcome to IPython. Our full documentation is available on ipython.readthedocs.io and contains info

Socorro Socorro is a Mozilla-centric ingestion pipeline and analysis tools for crash reports using the Breakpad libraries. Support This is a Mozilla-s

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 Viewflow is a framework built on the top of Airflow that enables data scientists to create materialized views. It allows data scientists to f

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the

TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl

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

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

iterative-stratification iterative-stratification is a project that provides scikit-learn compatible cross validators with stratification for multilab

combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License

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

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

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl

A lightweight, GPU accelerated, SQL engine built on the RAPIDS.ai ecosystem. Get Started on app.blazingsql.com Getting Started | Documentation | Examp

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

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. 10x Larger Models 10x Faster Trainin

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

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

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

seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr

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

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

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

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

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:

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technol

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

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 Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop work

geoplotlib is a python toolbox for visualizing geographical data and making maps data = read_csv('data/bus.csv') geoplotlib.dot(data) geoplotlib.show(

Location Data Visualization library for Jupyter Notebooks Library documentation at https://mapbox-mapboxgl-jupyter.readthedocs-hosted.com/en/latest/.

sentinelsat Sentinelsat makes searching, downloading and retrieving the metadata of Sentinel satellite images from the Copernicus Open Access Hub easy

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

EarthPy EarthPy makes it easier to plot and manipulate spatial data in Python. Why EarthPy? Python is a generic programming language designed to suppo

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

Fiona Fiona reads and writes geographic data files and thereby helps Python programmers integrate geographic information systems with other computer s

GeoPandas Python tools for geographic data Introduction GeoPandas is a project to add support for geographic data to pandas objects. It currently impl

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

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

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 is an open source stream processing framework with powerful stream- and batch-processing capabilities. Learn more about Flin

A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous

Broken Phone Recovery a guide how to backup data from your locked android phone if you broke your screen (and more) you can skip some steps depending

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

awesome-SynthText A curated list of awesome synthetic data for text location and recognition and OCR datasets. Text location SynthText SynthText_Chine

TextRecognitionDataGenerator A synthetic data generator for text recognition What is it for? Generating text image samples to train an OCR software. N

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

VistaOCR ISI's Optical Character Recognition (OCR) software for machine-print and handwriting data Publications "How to Efficiently Increase Resolutio

English | 简体中文 Introduction PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and a

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

Text language identification using Wikipedia data The aim of this project is to provide high-quality language detection over all the web's languages.

Overview ExtractTable - API to extract tabular data from images and scanned PDFs The motivation is to make it easy for developers to extract tabular d

Table of Contents Overview Requirements Demo Modules Overview This python package contains modules to help with finding and extracting tabular data fr

TableNet Unofficial implementation of ICDAR 2019 paper : TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from

Deep Learning framework for Line-level Handwritten Text Recognition Short presentation of our project Introduction Installation 2.a Install conda envi

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

dhSegment dhSegment is a tool for Historical Document Processing. Its generic approach allows to segment regions and extract content from different ty

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

DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain

tweetable-polyglot-png Pack up to 3MB of data into a tweetable PNG polyglot file. See it in action here: https://twitter.com/David3141593/status/13719

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.

Participants of Bertelsmann Technology Scholarship created an awesome list of resources and they want to share it with the world, if you find illegal

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

Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train