945 Repositories
Python series-classification Libraries
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language
Domain Generalization with MixStyle, ICLR'21.
MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?
Official implementation of "Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets" (CVPR2021)
Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract
Implementation of different ML Algorithms from scratch, written in Python 3.x
Implementation of different ML Algorithms from scratch, written in Python 3.x
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,
CorNet Correlation Networks for Extreme Multi-label Text Classification
CorNet Correlation Networks for Extreme Multi-label Text Classification Prerequisites python==3.6.3 pytorch==1.2.0 torchgpipe==0.0.5 click==7.0 ruamel
Reimplementation of the paper `Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? (ACL2020)`
Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper
ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期:ImageNet无限制对抗攻击 决赛第四名(team name: Advers)
Weakly supervised medical named entity classification
Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers
Implementation of Convolutional enhanced image Transformer
CeiT : Convolutional enhanced image Transformer This is an unofficial PyTorch implementation of Incorporating Convolution Designs into Visual Transfor
Visualize classified time series data with interactive Sankey plots in Google Earth Engine
sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P
An end-to-end PyTorch framework for image and video classification
What's New: March 2021: Added RegNetZ models November 2020: Vision Transformers now available, with training recipes! 2020-11-20: Classy Vision v0.5 R
Sandbox for training deep learning networks
Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"
Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F
Wetterdienst - Open weather data for humans
We are a group of like-minded people trying to make access to weather data in Python feel like a warm summer breeze, similar to other projects like rdwd for the R language, which originally drew our interest in this project.
3D ResNet Video Classification accelerated by TensorRT
Activity Recognition TensorRT Perform video classification using 3D ResNets trained on Kinetics-400 dataset and accelerated with TensorRT P.S Click on
Using multidimensional LSTM neural networks to create a forecast for Bitcoin price
Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co
Scalable, event-driven, deep-learning-friendly backtesting library
...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on
Get Landsat surface reflectance time-series from google earth engine
geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On
scalable analysis of images and time series
thunder scalable analysis of image and time series analysis in python Thunder is an ecosystem of tools for the analysis of image and time series data
Yet Another Time Series Model
Yet Another Timeseries Model (YATSM) master v0.6.x-maintenance Build Coverage Docs DOI | About Yet Another Timeseries Model (YATSM) is a Python packag
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification》(AAAI 2021) GitHub:
LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
Semi-supervised Learning for Sentiment Analysis
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.
An open-source library of algorithms to analyse time series in GPU and CPU.
Block-wisely Supervised Neural Architecture Search with Knowledge Distillation (CVPR 2020)
DNA This repository provides the code of our paper: Blockwisely Supervised Neural Architecture Search with Knowledge Distillation. Illustration of DNA
Examples and code for the Practical Machine Learning workshop series
Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D
The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.
Domain Generalization for Medical Imaging Classification with Linear Dependency Regularization The code release of paper 'Domain Generalization for Me
Library of various Few-Shot Learning frameworks for text classification
FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch
Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
scikit-learn cross validators for iterative stratification of multilabel data
iterative-stratification iterative-stratification is a project that provides scikit-learn compatible cross validators with stratification for multilab
Large-scale linear classification, regression and ranking in Python
lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con
High-level batteries-included neural network training library for Pytorch
Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st
PyTorch extensions for fast R&D prototyping and Kaggle farming
Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What
A python library for Bayesian time series modeling
PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W
AtsPy: Automated Time Series Models in Python (by @firmai)
Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp
A Python toolkit for rule-based/unsupervised anomaly detection in time series
Anomaly Detection Toolkit (ADTK) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.
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
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile
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
Python module for machine learning time series:
seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr
Time series forecasting with PyTorch
Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time
A Python package for time series classification
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 is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks
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
A python library for easy manipulation and forecasting of time series.
Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from
Probabilistic time series modeling in Python
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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
A unified framework for machine learning with time series
Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible
Automatic extraction of relevant features from time series:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
ARCH models in Python
arch Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python (with Cython and/or Numba used
Technical Analysis Library using Pandas and Numpy
Technical Analysis Library in Python It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Cl
a Deep Learning Framework for Text
DeLFT DeLFT (Deep Learning Framework for Text) is a Keras and TensorFlow framework for text processing, focusing on sequence labelling (e.g. named ent
Natural language detection
Detect the language of text. What’s so cool about franc? franc can support more languages(†) than any other library franc is packaged with support for
👄 The most accurate natural language detection library for Java and the JVM, suitable for long and short text alike
Quick Info this library tries to solve language detection of very short words and phrases, even shorter than tweets makes use of both statistical and
AntroPy: entropy and complexity of (EEG) time-series in Python
AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to e
DECAF: Deep Extreme Classification with Label Features
DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain
Implement face detection, and age and gender classification, and emotion classification.
YOLO Keras Face Detection Implement Face detection, and Age and Gender Classification, and Emotion Classification. (image from wider face dataset) Ove
Dogs classification with Deep Metric Learning using some popular losses
Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification.
Easy Few-Shot Learning Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
Automatic extraction of relevant features from time series:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. Blog posts Release 1.0.0 Fir
High performance datastore for time series and tick data
Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-
Python Library for Model Interpretation/Explanations
Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system
Gluon CV Toolkit
Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Open source time series library for Python
PyFlux PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
Code examples for my Write Better Python Code series on YouTube.
Write Better Python Code This repository contains the code examples used in my Write Better Python Code series published on YouTube: https:/
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
A modular single-molecule analysis interface
MOSAIC: A modular single-molecule analysis interface MOSAIC is a single molecule analysis toolbox that automatically decodes multi-state nanopore data
Automatic Video Library Manager for TV Shows. It watches for new episodes of your favorite shows, and when they are posted it does its magic.
Automatic Video Library Manager for TV Shows. It watches for new episodes of your favorite shows, and when they are posted it does its magic. Exclusiv
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing"
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind
Deepfake Scanner by Deepware.
Deepware Scanner (CLI) This repository contains the command-line deepfake scanner tool with the pre-trained models that are currently used at deepware
Implementation of TimeSformer, a pure attention-based solution for video classification
TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.
ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Get list of common stop words in various languages in Python
Python Stop Words Table of contents Overview Available languages Installation Basic usage Python compatibility Overview Get list of common stop words
Text vectorization tool to outperform TFIDF for classification tasks
WHAT: Supervised text vectorization tool Textvec is a text vectorization tool, with the aim to implement all the "classic" text vectorization NLP meth
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
Snips Python library to extract meaning from text
Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur
fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.
fastNLP fastNLP是一款轻量级的自然语言处理(NLP)工具包,目标是快速实现NLP任务以及构建复杂模型。 fastNLP具有如下的特性: 统一的Tabular式数据容器,简化数据预处理过程; 内置多种数据集的Loader和Pipe,省去预处理代码; 各种方便的NLP工具,例如Embedd
An open source library for deep learning end-to-end dialog systems and chatbots.
DeepPavlov is an open-source conversational AI library built on TensorFlow, Keras and PyTorch. DeepPavlov is designed for development of production re
Library for fast text representation and classification.
fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme
💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc