3149 Repositories
Python fast-data-pipeline Libraries
K Closest Points and Maximum Clique Pruning for Efficient and Effective 3D Laser Scan Matching (To appear in RA-L 2022)
KCP The official implementation of KCP: k Closest Points and Maximum Clique Pruning for Efficient and Effective 3D Laser Scan Matching, accepted for p
Python data loader for Solar Orbiter's (SolO) Energetic Particle Detector (EPD).
Data loader (and downloader) for Solar Orbiter/EPD energetic charged particle sensors EPT, HET, and STEP. Supports level 2 and low latency data provided by ESA's Solar Orbiter Archive.
Data Analytics on Genomes and Genetics
Data Analytics performed on On genomes and Genetics dataset to predict genetic disorder and disorder subclass. DONE by TEAM SIGMA!
Video Games Web Scraper is a project that crawls websites and APIs and extracts video game related data from their pages.
Video Games Web Scraper Video Games Web Scraper is a project that crawls websites and APIs and extracts video game related data from their pages. This
Predict the Site EUI, given the characteristics of the building and the weather data for the location of the building.
wids_datathon_2022 Description: Contains a data pipeline used to predict energy EUI Goals: Dataset exploration Automating the parameter fitting, gener
In this project , I play with the YouTube data API and extract trending videos in Nigeria on a particular day
YouTubeTrendingVideosAnalysis In this project , I played with the YouTube data API and extracted trending videos in Nigeria on a particular day. This
This repository structures data in title, summary, tags, sentiment given a fragment of a conversation
Understand-conversation-AI This repository structures data in title, summary, tags, sentiment given a fragment of a conversation How to install: pip i
Kinetics-Data-Preprocessing
Kinetics-Data-Preprocessing Kinetics-400 and Kinetics-600 are common video recognition datasets used by popular video understanding projects like Slow
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
Semi-Automated Data Processing
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
The bidirectional mapping library for Python.
bidict The bidirectional mapping library for Python. Status bidict: has been used for many years by several teams at Google, Venmo, CERN, Bank of Amer
Fast, efficient Blowfish cipher implementation in pure Python (3.4+).
blowfish This module implements the Blowfish cipher using only Python (3.4+). Blowfish is a block cipher that can be used for symmetric-key encryption
Python Library to get fast extensive Dummy Data for testing
Dumda Python Library to get fast extensive Dummy Data for testing https://pypi.org/project/dumda/ Installation pip install dumda Usage: Cities from d
Displaying plot of death rates from past years in Poland. Data source from these years is in readme
Average-Death-Rate Displaying plot of death rates from past years in Poland The goal collect the data from a CSV file count the ADR (Average Death Rat
Advanced raster and geometry manipulations
buzzard In a nutshell, the buzzard library provides powerful abstractions to manipulate together images and geometries that come from different kind o
Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.
Download and display GOES-East and GOES-West data GOES-East and GOES-West satellite data are made available on Amazon Web Services through NOAA's Big
Shelf DB is a tiny document database for Python to stores documents or JSON-like data
Shelf DB Introduction Shelf DB is a tiny document database for Python to stores documents or JSON-like data. Get it $ pip install shelfdb shelfquery S
Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle.
2019-indian-election-eda Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle. This project is a part of the Cou
DCM is a set of tools that helps you to keep your data in your Django Models consistent.
Django Consistency Model DCM is a set of tools that helps you to keep your data in your Django Models consistent. Motivation You have a lot of legacy
Check your accounts/tokens fast with our checker!
Discord_Account_Checker How to use? Installing library's pip install -r reqs.txt Loading accounts Load your accounts to accounts.txt file. Launch pyth
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
The RAP community of practice includes all analysts and data scientists who are interested in adopting the working practices included in reproducible analytical pipelines (RAP) at NHS Digital.
The RAP community of practice includes all analysts and data scientists who are interested in adopting the working practices included in reproducible analytical pipelines (RAP) at NHS Digital.
Data Science Course at Dept. of Computer Engineering, Chula 2022
2110446 Data Science Course at Chula 2022 Short links for exercises: Week1: Intro to Numpy, Pandas Numpy: https://colab.research.google.com/github/kao
Udacity - Data Analyst Nanodegree - Project 4 - Wrangle and Analyze Data
WeRateDogs Twitter Data from 2015 to 2017 Udacity - Data Analyst Nanodegree - Project 4 - Wrangle and Analyze Data Table of Contents Introduction Proj
A computer vision pipeline to identify the "icons" in Christian paintings
Christian-Iconography A computer vision pipeline to identify the "icons" in Christian paintings. A bit about iconography. Iconography is related to id
BSDotPy, A module to get a bombsquad player's account data.
BSDotPy BSDotPy, A module to get a bombsquad player's account data from bombsquad's servers. Badges Provided By: shields.io Acknowledgements Issues Pu
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a
Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation
Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation This repository contains code and data f
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec
HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti
Source code for the plant extraction workflow introduced in the paper “Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision”
Plant extraction workflow Source code for the plant extraction workflow introduced in the paper "Agricultural Plant Cataloging and Establishment of a
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Active Transport Analytics Model: A new strategic transport modelling and data visualization framework
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”
Historic weather - Home Assistant custom component for accessing historic weather data
Historic Weather for Home Assistant (CC) 2022 by Andreas Frisch github@fraxinas.
In this repo, I will put all the code related to data science using python libraries like Numpy, Pandas, Matplotlib, Seaborn and many more.
Python-for-DS In this repo, I will put all the code related to data science using python libraries like Numpy, Pandas, Matplotlib, Seaborn and many mo
This repository contains answers of the Shopify Summer 2022 Data Science Intern Challenge.
Data-Science-Intern-Challenge This repository contains answers of the Shopify Summer 2022 Data Science Intern Challenge. Summer 2022 Data Science Inte
Active Transport Analytics Model (ATAM) is a new strategic transport modelling and data visualization framework for Active Transport as well as emerging micro-mobility modes
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew
Validate arbitrary image uploads from incoming data urls while preserving file integrity but removing EXIF and unwanted artifacts and RCE exploit potential
Validate arbitrary base64-encoded image uploads as incoming data urls while preserving image integrity but removing EXIF and unwanted artifacts and mitigating RCE-exploit potential.
This is a simple website crawler which asks for a website link from the user to crawl and find specific data from the given website address.
This is a simple website crawler which asks for a website link from the user to crawl and find specific data from the given website address.
End-to-end MLOps pipeline of a BERT model for emotion classification.
image source EmoBERT-MLOps The goal of this repository is to build an end-to-end MLOps pipeline based on the MLOps course from Made with ML, but this
Deep learning with TensorFlow and earth observation data.
Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu
Big Data & Cloud Computing for Oceanography
DS2 Class 2022, Big Data & Cloud Computing for Oceanography Home of the 2022 ISblue Big Data & Cloud Computing for Oceanography class (IMT-A, ENSTA, I
Generating new names based on trends in data using GPT2 (Transformer network)
MLOpsNameGenerator Overall Goal The goal of the project is to develop a model that is capable of creating Pokémon names based on its description, usin
Official git for "CTAB-GAN: Effective Table Data Synthesizing"
CTAB-GAN This is the official git paper CTAB-GAN: Effective Table Data Synthesizing. The paper is published on Asian Conference on Machine Learning (A
A Python package that can be used to download post and comment data from Reddit.
Reddit Data Collector Reddit Data Collector is a Python package that allows a user to collect post and comment data from Reddit. It is built on top of
A practical ML pipeline for data labeling with experiment tracking using DVC.
Auto Label Pipeline A practical ML pipeline for data labeling with experiment tracking using DVC Goals: Demonstrate reproducible ML Use DVC to build a
A vanilla 3D face modeling on pose-invariant and multi-lightning image data
3D-Face-Modeling A vanilla 3D face modeling on pose-invariant and multi-lightning image data Table of Contents Background Install Usage Contributing B
🎁 3,000,000+ Unsplash images made available for research and machine learning
The Unsplash Dataset The Unsplash Dataset is made up of over 250,000+ contributing global photographers and data sourced from hundreds of millions of
A collection of machine learning examples and tutorials.
machine_learning_examples A collection of machine learning examples and tutorials.
Always know what to expect from your data.
Great Expectations Always know what to expect from your data. Introduction Great Expectations helps data teams eliminate pipeline debt, through data t
Jupyter notebook and datasets from the pandas Q&A video series
Python pandas Q&A video series Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas. Jupyter Note
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda
FMA: A Dataset For Music Analysis
FMA: A Dataset For Music Analysis Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. International Society for Music Information
A simple Blogging Backend app created with Fast API
This is a simple blogging app backend built with FastAPI. This project is created to simulate a real CRUD blogging system. It is built to be used by s
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
Predictive Modeling & Analytics on Home Equity Line of Credit
Predictive Modeling & Analytics on Home Equity Line of Credit Data (Python) HMEQ Data Set In this assignment we will use Python to examine a data set
Implements a fake news detection program using classifiers.
Fake news detection Implements a fake news detection program using classifiers for Data Mining course at UoA. Description The project is the categoriz
A collection of data structures and algorithms I'm writing while learning
Data Structures and Algorithms: This is a collection of data structures and algorithms that I write while learning the subject Stack: stack.py A stack
Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data
1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
Official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR)
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
Script that allows to download data with satellite's orbit height and create CSV with their change in time.
Satellite orbit height ◾ Requirements Python = 3.8 Packages listen in reuirements.txt (run pip install -r requirements.txt) Account on Space Track ◾
A tool for RaceRoom Racing Experience which shows you launch data
R3E Launch Tool A tool for RaceRoom Racing Experience which shows you launch data. Usage Run the tool, change the Stop Speed to whatever you want, and
This is a web scraper, using Python framework Scrapy, built to extract data from the Deals of the Day section on Mercado Livre website.
Deals of the Day This is a web scraper, using the Python framework Scrapy, built to extract data such as price and product name from the Deals of the
A Simple Key-Value Data-store written in Python
mercury-db This is a File Based Key-Value Datastore that supports basic CRUD (Create, Read, Update, Delete) operations developed using Python. The dat
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment. We need to predict whether the customer is going to reject the booking or not. Since in case of refusal, the hotel incurs losses.
Deep Learning pipeline for motor-imagery classification.
BCI-ToolBox 1. Introduction BCI-ToolBox is deep learning pipeline for motor-imagery classification. This repo contains five models: ShallowConvNet, De
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of
DeltaPy - Tabular Data Augmentation (by @firmai)
DeltaPy — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T
A Python package for time series augmentation
tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn
Supervised forecasting of sequential data in Python.
Supervised forecasting of sequential data in Python. Intro Supervised forecasting is the machine learning task of making predictions for sequential da
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour
Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to
Survival analysis in Python
What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
Forecast dynamically at scale with this unique package. pip install scalecast
🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels
Hierarchical Time Series Forecasting with a familiar API
scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to
An intuitive library to extract features from time series
Time Series Feature Extraction Library Intuitive time series feature extraction This repository hosts the TSFEL - Time Series Feature Extraction Libra
The Turing Change Point Detection Benchmark: An Extensive Benchmark Evaluation of Change Point Detection Algorithms on real-world data
Turing Change Point Detection Benchmark Welcome to the repository for the Turing Change Point Detection Benchmark, a benchmark evaluation of change po
Python binding for Khiva library.
Khiva-Python Build Documentation Build Linux and Mac OS Build Windows Code Coverage README This is the Khiva Python binding, it allows the usage of Kh
Timeseries analysis for neuroscience data
=================================================== Nitime: timeseries analysis for neuroscience data ===============================================
Python package for downloading ECMWF reanalysis data and converting it into a time series format.
ecmwf_models Readers and converters for data from the ECMWF reanalysis models. Written in Python. Works great in combination with pytesmo. Citation If
A way of looking at COVID-19 data that I haven't seen before.
Visualizing Omicron: COVID-19 Deaths vs. Cases Click here for other countries. Data is from Our World in Data/Johns Hopkins University. About this pro
Analyzed the data of VISA applicants to build a predictive model to facilitate the process of VISA approvals.
Analyzed the data of Visa applicants, built a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommended a suitable profile for the applicants for whom the visa should be certified or denied.
Medical appointments No-Show classifier
Medical Appointments No-shows Why do 20% of patients miss their scheduled appointments? A person makes a doctor appointment, receives all the instruct
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.
Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui
DevSecOps pipeline for Python based web app using Jenkins, Ansible, AWS, and open-source security tools and checks.
DevSecOps pipeline for Python Web App A Jenkins end-to-end DevSecOps pipeline for Python web application, hosted on AWS Ubuntu 20.04 Note: This projec
Prometheus Exporter for data scraped from datenplattform.darmstadt.de
darmstadt-opendata-exporter Scrapes data from https://datenplattform.darmstadt.de and presents it in the Prometheus Exposition format. Pull requests w
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers.
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
PyTorch EO aims to make Deep Learning for Earth Observation data easy and accessible to real-world cases and research alike.
Pytorch EO Deep Learning for Earth Observation applications and research. 🚧 This project is in early development, so bugs and breaking changes are ex
A library for fast parse & import of Windows Prefetch into Elasticsearch.
prefetch2es Fast import of Windows Prefetch(.pf) into Elasticsearch. prefetch2es uses C library libscca. Usage When using from the commandline interfa
Full-Stack application that visualizes amusement park safety.
Amusement Park Ride Safety Analysis Project Proposal We have chosen to look into amusement park data to explore ride safety relationships visually, in
This is the offline-training-pipeline for our project.
offline-training-pipeline This is the offline-training-pipeline for our project. We adopt the offline training and online prediction Machine Learning
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
General Assembly's 2015 Data Science course in Washington, DC
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (