Python NLU-training-data Resources

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

AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ [ICCV-2021]. Overview This package contains the model implementation and training

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.

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

RP-GAN: Stable GAN Training with Random Projections This repository contains a reference implementation of the algorithm described in the paper: Behna

Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G

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

DRAGAN (Deep Regret Analytic Generative Adversarial Networks) Link to our paper - https://arxiv.org/abs/1705.07215 Pytorch implementation (thanks!) -

code for "Improving GAN Training via Binarized Representation Entropy (BRE) Regularization" (ICLR2018 paper) paper: https://arxiv.org/abs/1805.03644 G

Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),

Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T

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

Status: Archive (code is provided as-is, no updates expected) improved-gan code for the paper "Improved Techniques for Training GANs" MNIST, SVHN, CIF

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

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

tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s

PhenoGraph for Python3 PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph ("network") repr

Description Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Ti

GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl

Calling Julia from Python - an experiment on data loading See the slides. TLDR After reading Patrick's blog post, we decided to try to replace C++ wit

High performance distributed framework for training deep learning recommendation models based on PyTorch.

The audio-video synchronization of MKV Container Format is exploited to achieve data hiding, where the hidden data can be utilized for various management purposes, including hyper-linking, annotation, and authentication

CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training This is the official repository for the code and models of the paper CCQA: A N

Housing Sensor Project The Urban Big Data Centre is conducting a study of indoor environmental data in Scottish houses. We are using Raspberry Pi devi

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

This repository contains all the experiments presented in the corresponding paper: "Scrutinizing XAI using linear ground-truth data with suppressor va

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

Code and data accompanying our SVRHM'21 paper. Requires tensorflow 1.13, python 3.7, scikit-learn, and pytorch 1.6.0 to be installed. Python scripts i

Automatically detecting anomalous exoplanet transits This repository contains the source code for the paper "Automatically detecting anomalous exoplan

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

DataCLUE: A Benchmark Suite for Data-centric NLP You can get the english version of README. 以数据为中心的AI测评(DataCLUE) 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE

Text2Music Emotion Embedding Text-to-Music Retrieval using Pre-defined/Data-driven Emotion Embeddings Reference Emotion Embedding Spaces for Matching

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

FLIR/DJI IR Camera Data Parser, Python Version Parser infrared camera data as NumPy data. Usage Clone this respository and cd thermal_parser. Run pip

liquid_scikit_learn Scikit learn library models to account for data and concept drift. This python library focuses on solving data drift and concept d

Data Loader Plugin - Python Table of Content (ToC) Data Loader Plugin - Python Table of Content (ToC) Overview References Python module Python virtual

Сервис для работы с открытыми данными Госдумы РФ Исходные данные из API Госдумы РФ извлекаются с помощью Apache Nifi и приземляются в хранилище Clickh

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

ObsPy is an open-source project dedicated to provide a Python framework for processing seismological data. It provides parsers for common file formats

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

A hands-off Anomaly Detection Library Table of contents What is Luminaire Quick Start Time Series Outlier Detection Workflow Anomaly Detection for Hig

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

findatapy findatapy creates an easy to use Python API to download market data from many sources including Quandl, Bloomberg, Yahoo, Google etc. using

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on streaming data.

Overview docs tests package Hangar is version control for tensor data. Commit, branch, merge, revert, and collaborate in the data-defined software era

sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical

ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi

Dagster An orchestration platform for the development, production, and observation of data assets. Dagster lets you define jobs in terms of the data f

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow

unyt A package for handling numpy arrays with units. Often writing code that deals with data that has units can be confusing. A function might return

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Data Science Cheatsheets List of Data Science Cheatsheets to rule the world. Table of Contents Business Science Business Science Problem Framework Dat

TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

ERFNet This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation. NEW!! New PyTorch

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

Identifies the faulty wafer before it can be used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells. The project retrains itself after every prediction, making it more robust and generalized over time.

Sentinel 2 Data Fetcher Installation Create a Virtual Environment and activate it. python3 -m venv venv . venv/bin/activate Install the Package via pi

OwO Encoder Very simple encoding scheme that will encode data as a series of OwOs or UwUs. The encoder is a simple state machine. Still needs a decode

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

Training BERT with Compute/Time (Academic) Budget This repository contains scripts for pre-training and finetuning BERT-like models with limited time

Sentiment analysis on streaming twitter data using Spark Structured Streaming & Python This project is a good starting point for those who have little

napari-time-slicer A meta plugin for processing timelapse data timepoint by timepoint. It enables a list of napari plugins to process 2D+t or 3D+t dat

Reproducibility materials for "Importance of Kernel Bandwidth in Quantum Machine Learning" Repo structure: code contains Python scripts used to genera

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

RMTD: Robust Moving Target Defence Against False Data Injection Attacks in Power Grids Real-time detection performance. This repo contains the code an

quick_eda Receiving dataframe statistics with one command Project description A python package for Data Scientists, Students, ML Engineers and anyone