6939 Repositories
Python deep-learning-library Libraries
Machine Learning for Time-Series with Python.Published by Packt
Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am
Deep Learning for Time Series Classification
Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re
U-Time: A Fully Convolutional Network for Time Series Segmentation
U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
Time series annotation library.
CrowdCurio Time Series Annotator Library The CrowdCurio Time Series Annotation Library implements classification tasks for time series. Features Suppo
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
A Multipurpose Library for Synthetic Time Series Generation in Python
TimeSynth Multipurpose Library for Synthetic Time Series Please cite as: J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library
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
A Time Series Library for Apache Spark
Flint: A Time Series Library for Apache Spark The ability to analyze time series data at scale is critical for the success of finance and IoT applicat
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
Library for time-series-forecasting-as-a-service.
TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi
Python implementation of the Learning Time-Series Shapelets method, that learns a shapelet-based time-series classifier with gradient descent.
shaplets Python implementation of the Learning Time-Series Shapelets method by Josif Grabocka et al., that learns a shapelet-based time-series classif
Whisper is a file-based time-series database format for Graphite.
Whisper Overview Whisper is one of three components within the Graphite project: Graphite-Web, a Django-based web application that renders graphs and
Elastic weight consolidation technique for incremental learning.
Overcoming-Catastrophic-forgetting-in-Neural-Networks Elastic weight consolidation technique for incremental learning. About Use this API if you dont
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
Automated Time Series Forecasting
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod
Machine Learning Time-Series Platform
cesium: Open-Source Platform for Time Series Inference Summary cesium is an open source library that allows users to: extract features from raw time s
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
(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
A python library for time-series smoothing and outlier detection in a vectorized way.
tsmoothie A python library for time-series smoothing and outlier detection in a vectorized way. Overview tsmoothie computes, in a fast and efficient w
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
Technical Analysis library in pandas for backtesting algotrading and quantitative analysis
bta-lib - A pandas based Technical Analysis Library bta-lib is pandas based technical analysis library and part of the backtrader family. Links Main P
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
A Python library for unevenly-spaced time series analysis
traces A Python library for unevenly-spaced time series analysis. Why? Taking measurements at irregular intervals is common, but most tools are primar
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
Code to accompany our paper "Continual Learning Through Synaptic Intelligence" ICML 2017
Continual Learning Through Synaptic Intelligence This repository contains code to reproduce the key findings of our path integral approach to prevent
PyTorch implementation of "Continual Learning with Deep Generative Replay", NIPS 2017
pytorch-deep-generative-replay PyTorch implementation of Continual Learning with Deep Generative Replay, NIPS 2017 Results Continual Learning on Permu
A PyTorch implementation of the continual learning experiments with deep neural networks
Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain
Software Engineer Salary Prediction
Based on 2021 stack overflow data, this machine learning web application helps one predict the salary based on years of experience, level of education and the country they work in.
A small Python library which gives you the IEEE-754 representation of a floating point number.
ieee754 ieee754 is small Python library which gives you the IEEE-754 representation of a floating point number. You can specify a precision given in t
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
Regularization and Feature Selection in Least Squares Temporal Difference Learning
Regularization and Feature Selection in Least Squares Temporal Difference Learning Description This is Python implementations of Least Angle Regressio
Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform sign language recognition.
Sign Language Recognition Service This is a Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform s
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
A small, Pygame-based library project intended for personal use.
EzyGame Version 0.0.1 A simple library project intended for personal use with Pygame. Warning: I am a very amateur programmer, so the code will probab
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
PASSL包含 SimCLR,MoCo,BYOL,CLIP等基于对比学习的图像自监督算法以及 Vision-Transformer,Swin-Transformer,BEiT,CVT,T2T,MLP_Mixer等视觉Transformer算法
PASSL Introduction PASSL is a Paddle based vision library for state-of-the-art Self-Supervised Learning research with PaddlePaddle. PASSL aims to acce
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
Repository of continual learning papers
Continual learning paper repository This repository contains an incomplete (but dynamically updated) list of papers exploring continual learning in ma
A modular, open and non-proprietary toolkit for core robotic functionalities by harnessing deep learning
A modular, open and non-proprietary toolkit for core robotic functionalities by harnessing deep learning Website • About • Installation • Using OpenDR
A self-supervised learning framework for audio-visual speech
AV-HuBERT (Audio-Visual Hidden Unit BERT) Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction Robust Self-Supervised A
A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.
The Top 10 Computer Vision Papers of 2021 The top 10 computer vision papers in 2021 with video demos, articles, code, and paper reference. While the w
A calibre plugin that generates Word Wise and X-Ray files then sends them to Kindle. Supports KFX, AZW3 and MOBI eBooks. X-Ray supports 18 languages.
WordDumb A calibre plugin that generates Word Wise and X-Ray files then sends them to Kindle. Supports KFX, AZW3 and MOBI eBooks. Languages X-Ray supp
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
Python meta class and abstract method library with restrictions.
abcmeta Python meta class and abstract method library with restrictions. This library provides a restricted way to validate abstract methods. The Pyth
PyPIContents is an application that generates a Module Index from the Python Package Index (PyPI) and also from various versions of the Python Standard Library.
PyPIContents is an application that generates a Module Index from the Python Package Index (PyPI) and also from various versions of the Python Standar
An Inverse Kinematics library aiming performance and modularity
IKPy Demo Live demos of what IKPy can do (click on the image below to see the video): Also, a presentation of IKPy: Presentation. Features With IKPy,
A simple wrapper to analyse and visualise reinforcement learning agents' behaviour in the environment.
Visrl Visrl (pronounced "visceral") is a simple wrapper to analyse and visualise reinforcement learning agents' behaviour in the environment. Reinforc
Covid-polygraph - a set of Machine Learning-driven fact-checking tools
Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.
Tutorial on scikit-learn and IPython for parallel machine learning
Parallel Machine Learning with scikit-learn and IPython Video recording of this tutorial given at PyCon in 2013. The tutorial material has been rearra
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 (
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
Data Science 45-min Intros Every week*, our data science team @Gnip (aka @TwitterBoulder) gets together for about 50 minutes to learn something. While
🔅 Shapash makes Machine Learning models transparent and understandable by everyone
🎉 What's new ? Version New Feature Description Tutorial 1.6.x Explainability Quality Metrics To help increase confidence in explainability methods, y
SphereFace: Deep Hypersphere Embedding for Face Recognition
SphereFace: Deep Hypersphere Embedding for Face Recognition By Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj and Le Song License SphereFa
Creative Applications of Deep Learning w/ Tensorflow
Creative Applications of Deep Learning w/ Tensorflow This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for th
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Here are the sections: Data Science Cheatsheets Data Science EBooks Data Science Question Bank Data Science Case Studies Data Science Portfolio Data J
Deep Learning Specialization by Andrew Ng, deeplearning.ai.
Deep Learning Specialization on Coursera Master Deep Learning, and Break into AI This is my personal projects for the course. The course covers deep l
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro
🤖 ⚡ scikit-learn tips
🤖 ⚡ scikit-learn tips New tips are posted on LinkedIn, Twitter, and Facebook. 👉 Sign up to receive 2 video tips by email every week! 👈 List of all
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
HackerMath for Machine Learning “Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” ― Richard
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Searches through git repositories for high entropy strings and secrets, digging deep into commit history
truffleHog Searches through git repositories for secrets, digging deep into commit history and branches. This is effective at finding secrets accident
Setup and customize deep learning environment in seconds.
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Hide screen when boss is approaching.
BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac
Not Suitable for Work (NSFW) classification using deep neural network Caffe models.
Open nsfw model This repo contains code for running Not Suitable for Work (NSFW) classification deep neural network Caffe models. Please refer our blo
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
Largest list of models for Core ML (for iOS 11+)
Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v
Distributed deep learning on Hadoop and Spark clusters.
Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version
My solution to the book A Collection of Data Science Take-Home Challenges
DS-Take-Home Solution to the book "A Collection of Data Science Take-Home Challenges". Note: Please don't contact me for the dataset. This repository
Automatic Video Library Manager for TV Shows
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. Dependen
Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Semantic Segmentation".
Dual Path Learning for Domain Adaptation of Semantic Segmentation Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Sema
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Official repository for "Orthogonal Projection Loss" (ICCV'21)
Orthogonal Projection Loss (ICCV'21) Kanchana Ranasinghe, Muzammal Naseer, Munawar Hayat, Salman Khan, & Fahad Shahbaz Khan Paper Link | Project Page
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders"
DECA Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders". All the code is writte
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility
PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility Jae Yong Lee, Joseph DeGol, Chuhang Zou, Derek Hoiem Installation To install nece
Implementation of Cross-category Video Highlight Detection via Set-based Learning (ICCV 2021).
Cross-category Video Highlight Detection via Set-based Learning Introduction This project is an implementation of ``Cross-category Video Highlight Det
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization
FAC-Net Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization Linjiang Huang (CUHK), Liang Wang (CASIA), Hongsheng
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
PyTorch implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021)
MT-ORL: Multi-Task Occlusion Relationship Learning Official implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021) P
Resco: A simple python package that report the effect of deep residual learning
resco Description resco is a simple python package that report the effect of dee
Moon-patrol - A faithful recreation of the 1983 hit classic Moon Patrol for the Atari 2600 created using the Pygame library for Python
Moon Patrol A recreation of the hit Atari 2600 game, Moon Patrol Moon Patrol is
deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and different optimization choices
deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.
Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u
Source code for Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active Learning - Official Pytorch implementation of the CVPR 2021 paper Kwanyoung Kim, Dongwon Park, Kwang In Kim,
Sequential GCN for Active Learning
Sequential GCN for Active Learning Please cite if using the code: Link to paper. Requirements: python 3.6+ torch 1.0+ pip libraries: tqdm, sklearn, sc
Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented at RAI 2021.
Can Active Learning Preemptively Mitigate Fairness Issues? Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented a
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active Learning Code for SRAAL [2020 CVPR Oral] Requirements torch = 1.6.0 numpy = 1.19.1 tqdm = 4.31.1 AL Results The
An implementation of the BADGE batch active learning algorithm.
Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o