Python Data-manipulation Resources

Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

Nuance I use Nuance to curate varied visualization thoughts during my data scientist career. It is not yet a package but a list of small ideas. Welcom

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

A program that analyzes data from inertia measurement units installeed in aircraft and generates g-exceedance curves

radiale what if home-automation was also homoiconic? The upper or proximal row contains three bones, to which Gegenbaur has applied the terms radiale,

Byte Steganography Image/Data Injector. For artists or people to inject their own print/data into their images. TODO Add more file formats to support.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

Facebook Scraper Use Flask API to wrap Facebook data. Grab the wapper of Facebook public pages without an API key. (Currently working 2021) Setup Befo

Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa

accsr This lightweight library contains utilities for managing, loading, uploading, opening and generally wrangling data and configurations. It was ba

BENDR BErt-like Neurophysiological Data Representation This repository contains the source code for reproducing, or extending the BERT-like self-super

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and

MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant

sqliteBasics create a database, insert data and easily select it with Sqlite Watch on YouTube a step by step tutorial explaining this code: https://yo

insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper

foamTEX An open source utility for creating publication quality LaTex figures generated from OpenFOAM data files. Explore the docs » Report Bug · Requ

DBMS project- Hotel Franchise Data and application project By TEAM Kurukunda Bhargavi Pamulapati Pallavi Greeshma Amaraneni What is this project about

Sheet Data Image/PDF-to-CSV Converter

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

'db' within pydantic - A single model for shaping, creating, accessing, storing data within a Database Key Features Integrated Redis Caching Support A

This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.

datasketch: Big Data Looks Small datasketch gives you probabilistic data structures that can process and search very large amount of data super fast,

AugMix Introduction We propose AugMix, a data processing technique that mixes augmented images and enforces consistent embeddings of the augmented ima

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Youtube video details analyser Steps to run this project Please set the AuthKey which you can fetch from google developer console and paste it in the

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Predicting Yelp Review Quality Table of Contents Introduction Motivation Goal and Central Questions The Data Data Storage and ETL EDA Data Pipeline Da

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

Python Business Analytics Also instead of "watching" you can join the link-letter, it's already being sent out to about 90 people and you are free to

Python Data Science Handbook This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. How to Use th

Design and build a wrapper for the Open Weather API current weather data service that returns a city's temperature, with caching, also allowing for the temperature of the latest queried cities that are still validly cached to be retrieved.

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

Clinica Software platform for clinical neuroimaging studies Homepage | Documentation | Paper | Forum | See also: AD-ML, AD-DL ClinicaDL About The Proj

Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla

Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-

Create postgres tables from CSV files This first section is only relate to creating tables from CSV files using postgres container alone. Just one of

For specific function. For my own convenience. Remind owner to share data to another DITO user.

This project contains the process from building a web crawler to extract the raw data of house price to create ETL pipelines using Google Could Platform services.

NLP Space News Topic Modeling Photos by nasa.gov (1, 2, 3, 4, 5) and extremetech.com Table of Contents Project Idea Data acquisition Primary data sour

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro

EmeraldML A machine learning library for streamlining the process of (1) cleaning and splitting data, (2) training, optimizing, and testing various mo

Problems and it's solutions. Problem solving, a great Speed comes with a good Accuracy. The more Accurate you can write code, the more Speed you will

Balanced-Evolutionary-Semi-Stacking Code for the paper ''BESS: Balanced Evolutionary Semi-Stacking for Disease Detection via Partially Labeled Imbalan

go-cqhttp API typing annoations, return data models and utils for nonebot

Transfiere eventos de Sucuri hacia Azure Data Tables Script para transferir eventos del Sucuri Web Application Firewall (WAF) hacia Azure Data Tables,

FakeDataGen is a Full Valid Fake Data Generator. This tool helps you to create fake accounts (in Spanish format) with fully valid data. Within this in

sparqlfun LinkML based SPARQL template library and execution engine modularized core library of SPARQL templates generic templates using common vocabs

JSONObjectMapper Allows you to transform JSON data into an object whose members can be queried using the member access operator. Unlike json.dumps in

A benchmark of data-centric tasks from across the machine learning lifecycle.

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with

ML Privacy Meter Machine learning is playing a central role in automated decision making in a wide range of organization and service providers. The da

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le

PyJava This library is an ongoing effort towards bringing the data exchanging ability between Java/Scala and Python

A number of methods in order to perform Natural Language Processing on live data derived from Twitter

CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021

braintransform Project issue to website data transformation toolkit. Introduction The purpose of these scripts is to be able to dynamically generate t

Simulation Dataset for BBHnet NOTE: OLD README, UPDATE IN PROGRESS We generate simulation dataset to train BBHnet, our deep learning framework for det

Clip Bing Maps backgound as RGB geotif image using center-point from vector data of a shapefile and Bing Maps zoom. Also, rasterize shapefile vectors as corresponding label image.

PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.

GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data By Shuchang Zhou, Taihong Xiao, Yi Yang, Dieqiao Feng, Qinyao He, W

ComboGAN This is our ongoing PyTorch implementation for ComboGAN. Code was written by Asha Anoosheh (built upon CycleGAN) [ComboGAN Paper] If you use

News 11 Jan 2020: We clean up the code to make it more readable! The old version is here: v1. AttGAN TIP Nov. 2019, arXiv Nov. 2017 TensorFlow impleme

deep-photo-styletransfer Code and data for paper "Deep Photo Style Transfer" Disclaimer This software is published for academic and non-commercial use

CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for

FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

This piece of code is a User Welcomer with Image Manipulation using Python and Pillow (PIL).

nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom

Housegan-data-reader House-GAN++ (data-reader) Code and instructions for converting rplan dataset (raster images) to housegan++ data format. House-GAN

MONEYBALL - ChatBot Module: 4006CEM, Class: B, Group: 5 Contributors: Jonas Djondo Roshan Kc Cole Samson Daniel Rodrigues Ihteshaam Naseer Kind remind

Use this repository to easily convert your source files (csv, txt, excel, json, html) into record-oriented JSON files that can be uploaded into onetask.

Finding Label and Model Errors in Perception Data With Learned Observation Assertions This is the project page for Finding Label and Model Errors in P

🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort

This is the code used in the paper "Entity Embeddings of Categorical Variables". If you want to get the original version of the code used for the Kagg

MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals (or prediction sets) using your favourit

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.

FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu