3196 Repositories
Python data-processing Libraries
MS in Data Science capstone project. Studying attacks on autonomous vehicles.
Surveying Attack Models for CAVs Guide to Installing CARLA and Collecting Data Our project focuses on surveying attack models for Connveced Autonomous
Pipeline for training LSA models using Scikit-Learn.
Latent Semantic Analysis Pipeline for training LSA models using Scikit-Learn. Usage Instead of writing custom code for latent semantic analysis, you j
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
English|简体中文 ERNIE是百度开创性提出的基于知识增强的持续学习语义理解框架,该框架将大数据预训练与多源丰富知识相结合,通过持续学习技术,不断吸收海量文本数据中词汇、结构、语义等方面的知识,实现模型效果不断进化。ERNIE在累积 40 余个典型 NLP 任务取得 SOTA 效果,并在 G
Revisiting Pre-trained Models for Chinese Natural Language Processing (Findings of EMNLP 2020)
This repository contains the resources in our paper "Revisiting Pre-trained Models for Chinese Natural Language Processing", which will be published i
SentAugment is a data augmentation technique for semi-supervised learning in NLP.
SentAugment SentAugment is a data augmentation technique for semi-supervised learning in NLP. It uses state-of-the-art sentence embeddings to structur
Creating predictive checklists from data using integer programming.
Learning Optimal Predictive Checklists A Python package to learn simple predictive checklists from data subject to customizable constraints. For more
Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]
Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi
A simple algorithm for extracting tree height in sparse scene from point cloud data.
TREE HEIGHT EXTRACTION IN SPARSE SCENES BASED ON UAV REMOTE SENSING This is the offical python implementation of the paper "Tree Height Extraction in
My notes on Data structure and Algos in golang implementation and python
My notes on DS and Algo Table of Contents Arrays LinkedList Trees Types of trees: Tree/Graph Traversal Algorithms Heap Priorty Queue Trie Graphs Graph
Minimal pure Python library for working with little-endian list representation of bit strings.
bitlist Minimal Python library for working with bit vectors natively. Purpose This library allows programmers to work with a native representation of
Google, Facebook, Amazon, Microsoft, Netflix tech interview questions
Algorithm and Data Structures Interview Questions HackerRank | Practice, Tutorials & Interview Preparation Solutions This repository consists of solut
Learn to code in any language. If
Learn to Code It is an intiiative undertaken by Student Ambassadors Club, Jamshoro for students who are absolute begineers in programming and want to
Multiple Imputation with Random Forests in Python
miceforest: Fast, Memory Efficient Imputation with lightgbm Fast, memory efficient Multiple Imputation by Chained Equations (MICE) with lightgbm. The
Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from time series data.
ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t
Very useful and necessary functions that simplify working with data
Additional-function-for-pandas Very useful and necessary functions that simplify working with data random_fill_nan(module_name, nan) - Replaces all sp
Makes google's political ad database actually useful
Making Google's political ad transparency library suck less This is a series of scripts that takes Google's political ad transparency data and makes t
A tool to nowcast quarterly data with monthly indicators: US consumption example
MIDAS_Nowcaster A tool to nowcast quarterly data with monthly indicators: US consumption example Pulls data directly from FRED from a list of codes -
Data Exfiltration without ever making a connection. Using TCP header space.
TCPwned PoC toy code to exfiltrate data without ever making a TCP connection. This will never show up in firewall logs, much less, actually be monitor
Upgini : data search library for your machine learning pipelines
Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Open source annotation tool for machine learning practitioners.
doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ
Tools for curating biomedical training data for large-scale language modeling
Tools for curating biomedical training data for large-scale language modeling
Code for Editing Factual Knowledge in Language Models
KnowledgeEditor Code for Editing Factual Knowledge in Language Models (https://arxiv.org/abs/2104.08164). @inproceedings{decao2021editing, title={Ed
A Model for Natural Language Attack on Text Classification and Inference
TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re
The repository for the paper "When Do You Need Billions of Words of Pretraining Data?"
pretraining-learning-curves This is the repository for the paper When Do You Need Billions of Words of Pretraining Data? Edge Probing We use jiant1 fo
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat
Code associated with the Don't Stop Pretraining ACL 2020 paper
dont-stop-pretraining Code associated with the Don't Stop Pretraining ACL 2020 paper Citation @inproceedings{dontstoppretraining2020, author = {Suchi
Training and evaluation codes for the BertGen paper (ACL-IJCNLP 2021)
BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.
Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho
The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.
Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]
DANeS is an open-source E-newspaper dataset by collaboration between DATASET JSC (dataset.vn) and AIV Group (aivgroup.vn)
DANeS - Open-source E-newspaper dataset Source: Technology vector created by macrovector - www.freepik.com. DANeS is an open-source E-newspaper datase
clustimage is a python package for unsupervised clustering of images.
clustimage The aim of clustimage is to detect natural groups or clusters of images. Image recognition is a computer vision task for identifying and ve
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types
Data preprocessing rosetta parser for python
datapreprocessing_rosetta_parser I've never done any NLP or text data processing before, so I wanted to use this hackathon as a learning opportunity,
Async boto3 with Autogenerated Data Classes
awspydk Async boto3 with Autogenerated JIT Data Classes Motivation This library is forked from an internal project that works with a lot of backend AW
A command line tool that creates a super timeline from SentinelOne's Deep Visibility data
S1SuperTimeline A command line tool that creates a super timeline from SentinelOne's Deep Visibility data What does it do? The script accepts a S1QL q
Visualize your pandas data with one-line code
PandasEcharts 简介 基于pandas和pyecharts的可视化工具 安装 pip 安装 $ pip install pandasecharts 源码安装 $ git clone https://github.com/gamersover/pandasecharts $ cd pand
A Pythonic framework for threat modeling
pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Implementation of Neonatal Seizure Detection using EEG signals for deploying on edge devices including Raspberry Pi.
NeonatalSeizureDetection Description Link: https://arxiv.org/abs/2111.15569 Citation: @misc{nagarajan2021scalable, title={Scalable Machine Learn
Official Repository for "Robust On-Policy Data Collection for Data Efficient Policy Evaluation" (NeurIPS 2021 Workshop on OfflineRL).
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation Source code of Robust On-Policy Data Collection for Data-Efficient Policy Evalua
Self-Supervised Image Denoising via Iterative Data Refinement
Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S
Data Consistency for Magnetic Resonance Imaging
Data Consistency for Magnetic Resonance Imaging Data Consistency (DC) is crucial for generalization in multi-modal MRI data and robustness in detectin
Automatic Data-Regularized Actor-Critic (Auto-DrAC)
Auto-DrAC: Automatic Data-Regularized Actor-Critic This is a PyTorch implementation of the methods proposed in Automatic Data Augmentation for General
PyContinual (An Easy and Extendible Framework for Continual Learning)
PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read
Code to produce syntactic representations that can be used to study syntax processing in the human brain
Can fMRI reveal the representation of syntactic structure in the brain? The code base for our paper on understanding syntactic representations in the
This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"
BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience This repository is the official implementation of [https://www.bi
Auditing Black-Box Prediction Models for Data Minimization Compliance
Data-Minimization-Auditor An auditing tool for model-instability based data minimization that is introduced in "Auditing Black-Box Prediction Models f
[NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators"
G-PATE This is the official code base for our NeurIPS 2021 paper: "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of T
TAUFE: Task-Agnostic Undesirable Feature DeactivationUsing Out-of-Distribution Data
A deep neural network (DNN) has achieved great success in many machine learning tasks by virtue of its high expressive power. However, its prediction can be easily biased to undesirable features, which are not essential for solving the target task and are even imperceptible to a human, thereby resulting in poor generalization
Equivariant layers for RC-complement symmetry in DNA sequence data
Equi-RC Equivariant layers for RC-complement symmetry in DNA sequence data This is a repository that implements the layers as described in "Reverse-Co
Hide sensitive information in images
Data-Preserved Script allowing to blur the most sensitive information on images. Prerequisites Before you begin, ensure you have met the following req
Official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021.
Introduction This repository is the official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021. Data-free Kno
A paper list of pre-trained language models (PLMs).
Large-scale pre-trained language models (PLMs) such as BERT and GPT have achieved great success and become a milestone in NLP.
Sign data using symmetric-key algorithm encryption.
Sign data using symmetric-key algorithm encryption. Validate signed data and identify possible validation errors. Uses sha-(1, 224, 256, 385 and 512)/hmac for signature encryption. Custom hash algorithms are allowed. Useful shortcut functions for signing (and validating) dictionaries and URLs.
A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms
MatrixProfile MatrixProfile is a Python 3 library, brought to you by the Matrix Profile Foundation, for mining time series data. The Matrix Profile is
Various Algorithms for Short Text Mining
Short Text Mining in Python Introduction This package shorttext is a Python package that facilitates supervised and unsupervised learning for short te
Primitives for machine learning and data science.
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt
Memory tests solver with using OpenCV
Human Benchmark project This project is OpenCV based programs which are puzzle solvers for 7 different games for https://humanbenchmark.com/. made as
An helper library to scrape data from Instagram effortlessly, using the Influencer Hunters APIs.
Instagram Scraper An utility library to scrape data from Instagram hassle-free Go to the website » View Demo · Report Bug · Request Feature About The
tradingview socket api for fetching real time prices.
tradingView-API tradingview socket api for fetching real time prices. How to run git clone https://github.com/mohamadkhalaj/tradingView-API.git cd tra
This repository is used to provide data to zzhack,
This repository is used to provide data to zzhack, but you don't have to care about anything, just write your thinking down, and you can see your thinking is rendered in zzhack perfectly
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository provides the official PyTorch implementation
Scrapping the data from each page of biocides listed on the BAUA website into a csv file
Scrapping the data from each page of biocides listed on the BAUA website into a csv file
Experiments with Fourier layers on simulation data.
Factorized Fourier Neural Operators This repository contains the code to reproduce the results in our NeurIPS 2021 ML4PS workshop paper, Factorized Fo
The first GANs-based omics-to-omics translation framework
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
Auxiliary data to the CHIIR paper Searching to Learn with Instructional Scaffolding
Searching to Learn with Instructional Scaffolding This is the data and analysis code for the paper "Searching to Learn with Instructional Scaffolding"
Source Code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question Matching
Description The source code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chin
A program that analyzes data from inertia measurement units installed in aircraft and generates g-exceedance curves.
A program that analyzes data from inertia measurement units installed in aircraft and generates g-exceedance curves.
Data wrangling & common calculations for results from qMem measurement software
qMem Datawrangler This script processes output of qMem measurement software into an Origin ® compatible *.csv files and matplotlib graphs to quickly v
Django based webapp pulling in crypto news and price data via api
Deploy Django in Production FTA project implementing containerization of Django Web Framework into Docker to be placed into Azure Container Services a
Python tools for 3D face: 3DMM, Mesh processing(transform, camera, light, render), 3D face representations.
face3d: Python tools for processing 3D face Introduction This project implements some basic functions related to 3D faces. You can use this to process
Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.
SynthText Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Ved
🛰️ Scripts démontrant l'utilisation de l'imagerie RADARSAT-1 à partir d'un seau AWS | 🛰️ Scripts demonstrating the use of RADARSAT-1 imagery from an AWS bucket
🛰️ Scripts démontrant l'utilisation de l'imagerie RADARSAT-1 à partir d'un seau AWS | 🛰️ Scripts demonstrating the use of RADARSAT-1 imagery from an AWS bucket
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER. @inproceedings{tedes
This is a python script to grab data from Zyxel NSA310 NAS and display in Home Asisstant as sensors.
Home-Assistant Python Scripts Python Scripts for Home-Assistant (http://www.home-assistant.io) Zyxel-NSA310-Home-Assistant Monitoring This is a python
A real world application of a Recurrent Neural Network on a binary classification of time series data
What is this This is a real world application of a Recurrent Neural Network on a binary classification of time series data. This project includes data
APIlocal_dbAWS_RDS - Disclaimer! All data used is for educational purposes only.
APIlocal_dbAWS_RDS Disclaimer! All data used is for educational purposes only. ETL pipeline diagram. Aim of project By creating a fully working pipe
Flexible time series feature extraction & processing
tsflex is a toolkit for flexible time series processing & feature extraction, that is efficient and makes few assumptions about sequence data. Useful
DuBE: Duple-balanced Ensemble Learning from Skewed Data
DuBE: Duple-balanced Ensemble Learning from Skewed Data "Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning" (IEEE ICDE 2022 S
Fast mesh denoising with data driven normal filtering using deep variational autoencoders
Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh
IMBENS: class-imbalanced ensemble learning in Python.
IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".
Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer
Deep Learning Emotion decoding using EEG data from Autism individuals
Deep Learning Emotion decoding using EEG data from Autism individuals This repository includes the python and matlab codes using for processing EEG 2D
This repository contains all code and data for the Inside Out Visual Place Recognition task
Inside Out Visual Place Recognition This repository contains code and instructions to reproduce the results for the Inside Out Visual Place Recognitio
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data Authors: Yi-Chang Chen, Yu-Chuan Chang, Yen-Cheng Chang and Yi-Ren Ye
Tool for running a high throughput data ingestion/transformation workload with MongoDB
Mongo Mangler The mongo-mangler tool is a lightweight Python utility, which you can run from a low-powered machine to execute a high throughput data i
Gathering data of likes on Tinder within the past 7 days
tinder_likes_data Gathering data of Likes Sent on Tinder within the past 7 days. Versions November 25th, 2021 - Functionality to get the name and age
Empresas do Brasil (CNPJs)
Biblioteca em Python que coleta informações cadastrais de empresas do Brasil (CNPJ) obtidas de fontes oficiais (Receita Federal) e exporta para um formato legível por humanos (CSV ou JSON).
E-Commerce recommender demo with real-time data and a graph database
🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str
An optimized prompt tuning strategy comparable to fine-tuning across model scales and tasks.
P-tuning v2 P-Tuning v2: Prompt Tuning Can Be Comparable to Finetuning Universally Across Scales and Tasks An optimized prompt tuning strategy achievi
Redis OM Python makes it easy to model Redis data in your Python applications.
Object mapping, and more, for Redis and Python Redis OM Python makes it easy to model Redis data in your Python applications. Redis OM Python | Redis
A procedural Blender pipeline for photorealistic training image generation
BlenderProc2 A procedural Blender pipeline for photorealistic rendering. Documentation | Tutorials | Examples | ArXiv paper | Workshop paper Features
Napari simpleitk image processing
napari-simpleitk-image-processing (n-SimpleITK) Process images using SimpleITK in napari Usage Filters of this napari plugin can be found in the Tools
Open source platform for Data Science Management automation
Hydrosphere examples This repo contains demo scenarios and pre-trained models to show Hydrosphere capabilities. Data and artifacts management Some mod
Training open neural machine translation models
Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Learning from graph data using Keras
Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda