1792 Repositories
Python TensorFlow-Time-Series-Examples Libraries
A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.
TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction ่ฎบๆ๏ผTime Interval Aware Sel
TensorFlow port of PyTorch Image Models (timm) - image models with pretrained weights.
TensorFlow-Image-Models Introduction Usage Models Profiling License Introduction TensorfFlow-Image-Models (tfimm) is a collection of image models with
A Python implementation of GRAIL, a generic framework to learn compact time series representations.
GRAIL A Python implementation of GRAIL, a generic framework to learn compact time series representations. Requirements Python 3.6+ numpy scipy tslearn
A tool to estimate time varying instantaneous reproduction number during epidemics
EpiEstim A tool to estimate time varying instantaneous reproduction number during epidemics. It is described in the following paper: @article{Cori2013
Pysces (read: Pisces) is a program to help you send emails with an user-customizable time-based scheduling.
Pysces (Python Scheduled-Custom-Email-Sender) Pysces (read: Pisces) is a program to help you send emails with an user-customizable time-based email se
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati
Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)
This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to plane. The second method utilizes voxel adjacency, and fit to plane.
Code repository for "It's About Time: Analog clock Reading in the Wild"
it's about time Code repository for "It's About Time: Analog clock Reading in the Wild" Packages required: pytorch (used 1.9, any reasonable version s
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
A Python package to preprocess time series
Disclaimer: This package is WIP. Do not take any APIs for granted. tspreprocess Time series can contain noise, may be sampled under a non fitting rate
Python implementation of "Elliptic Fourier Features of a Closed Contour"
PyEFD An Python/NumPy implementation of a method for approximating a contour with a Fourier series, as described in [1]. Installation pip install pyef
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and
Unofficial keras(tensorflow) implementation of MAE model from Masked Autoencoders Are Scalable Vision Learners
MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been
Tensorflow 2.x implementation of Vision-Transformer model
Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT
State of the art faster Natural Language Processing in Tensorflow 2.0 .
tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
An open-source, low-code machine learning library in Python ๐ Version 2.3.5 out now! Check out the release notes here. Official โข Docs โข Install โข Tu
[ICML 2021] A fast algorithm for fitting robust decision trees.
GROOT: Growing Robust Trees Growing Robust Trees (GROOT) is an algorithm that fits binary classification decision trees such that they are robust agai
ETNA โ time series forecasting framework
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
SHIBgreen is a cryptocurrency forked from Chia and uses the Proof of Space and Time consensus algorithm
SHIBgreen is a cryptocurrency forked from Chia and uses the Proof of Space and Time consensus algorithm
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
2D fluid simulation implementation of Jos Stam paper on real-time fuild dynamics, including some suggested extensions.
Fluid Simulation Usage Download this repo and store it in your computer. Open a terminal and go to the root directory of this folder. Make sure you ha
A basic Ray Tracer that exploits numpy arrays and functions to work fast.
Python-Fast-Raytracer A basic Ray Tracer that exploits numpy arrays and functions to work fast. The code is written keeping as much readability as pos
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
A keras-based real-time model for medical image segmentation (CFPNet-M)
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat
TensorFlow implementation of Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction)
Barlow-Twins-TF This repository implements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrat
Management of exclusive GPU access for distributed machine learning workloads
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
Friday Night Funkin - converts a chart from 4/4 time to 6/8 time, or from regular to swing tempo.
Chart to swing converter As seen in https://twitter.com/i_winxd/status/1462220493558366214 A program written in python that converts a chart from 4/4
Cascaded Pyramid Network (CPN) based on Keras (Tensorflow backend)
ML2 Takehome Project Reimplementing the paper: Cascaded Pyramid Network for Multi-Person Pose Estimation Dataset The model uses the COCO dataset which
A crash course in six episodes for software developers who want to become machine learning practitioners.
Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex
A simple, fully convolutional model for real-time instance segmentation.
You Only Look At CoefficienTs โโโ โโโ โโโโโโโ โโโ โโโโโโ โโโโโโโโโโโโโโโโ โโโโ โโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโ โโโ
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.
SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S
Multiple implementations for abstractive text summurization , using google colab
Text Summarization models if you are able to endorse me on Arxiv, i would be more than glad https://arxiv.org/auth/endorse?x=FRBB89 thanks This repo i
NLP and Text Generation Experiments in TensorFlow 2.x / 1.x
Code has been run on Google Colab, thanks Google for providing computational resources Contents Natural Language Processing๏ผ่ช็ถ่ฏญ่จๅค็๏ผ Text Classificati
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Introduction XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective.
TensorFlow code and pre-trained models for BERT
BERT ***** New March 11th, 2020: Smaller BERT Models ***** This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece
Lab Materials for MIT 6.S191: Introduction to Deep Learning
This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning
TensorFlow Tutorials with YouTube Videos
TensorFlow Tutorials Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction These tutorials are intended for beginne
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
Binary LSTM model for text classification
Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
Properly-formatted dynamic timestamps for Discord messages
discord-timestamps discord-timestamps generates properly-formatted dynamic timestamps for Discord messages, with support for Arrow objects. format
Real-time analysis of intracranial neurophysiology recordings.
py_neuromodulation Click this button to run the "Tutorial ML with py_neuro" notebooks: The py_neuromodulation toolbox allows for real time capable pro
An interview engine for businesses, interview those who are actually qualified and are worth your time!
easyInterview V0.8B An interview engine for businesses, interview those who are actually qualified and are worth your time! Quick Overview You/the com
Sukoku-solver Python About Sudoku is one of the most popular puzzle games of all time
Sukoku-solver Python About Sudoku is one of the most popular puzzle games of all time. As a logic puzzle, Sudoku is also an excellent brain game. Bein
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.
AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video Timely handgun detection is a cr
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut
Learning kernels to maximize the power of MMD tests
Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei*, Maya Kabkab*, Rama Chellappa [*: authors co
Bayesian Generative Adversarial Networks in Tensorflow
Bayesian Generative Adversarial Networks in Tensorflow This repository contains the Tensorflow implementation of the Bayesian GAN by Yunus Saatchi and
๐ฅ3D-RecGAN in Tensorflow (ICCV Workshops 2017)
3D Object Reconstruction from a Single Depth View with Adversarial Learning Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, Niki Trigoni
ARAE-Tensorflow for Discrete Sequences (Adversarially Regularized Autoencoder)
ARAE Tensorflow Code Code for the paper Adversarially Regularized Autoencoders for Generating Discrete Structures by Zhao, Kim, Zhang, Rush and LeCun
Tensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)
tf-SNDCGAN Tensorflow implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (https://www.researchgate.net/publicati
TensorFlow implementation of Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently.
Adversarial Chess TensorFlow implementation of Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently. Requirements To run
TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"
Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
Image Completion with Deep Learning in TensorFlow
Image Completion with Deep Learning in TensorFlow See my blog post for more details and usage instructions. This repository implements Raymond Yeh and
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
MGANs Training & Testing code (torch), pre-trained models and supplementary materials for "Precomputed Real-Time Texture Synthesis with Markovian Gene
Text to image synthesis using thought vectors
Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations.
IllustrationGAN A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations. Generated Images
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(ๅญๅฐๅญ, me
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq
EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
EfficientDet This is an implementation of EfficientDet for object detection on Keras and Tensorflow. The project is based on the official implementati
Lightweight Python library for adding real-time object tracking to any detector.
Norfair is a customizable lightweight Python library for real-time 2D object tracking. Using Norfair, you can add tracking capabilities to any detecto
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
๐ Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Collection of generative models in Tensorflow
tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th
Build Graph Nets in Tensorflow
Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
Description Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Ti
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 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
Hierarchical Time Series Forecasting using Prophet
htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th
Time Series Prediction with tf.contrib.timeseries
TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas
Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.
GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl
Real-time 3D multi-person detection made easy with OpenPose and the ZED
OpenPose ZED This sample show how to simply use the ZED with OpenPose, the deep learning framework that detects the skeleton from a single 2D image. T
A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body
DensePose: Dense Human Pose Estimation In The Wild Rฤฑza Alp Gรผler, Natalia Neverova, Iasonas Kokkinos [densepose.org] [arXiv] [BibTeX] Dense human pos
Human Pose estimation with TensorFlow framework
Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and
Implementation of light baking system for ray tracing based on Activision's UberBake
Vulkan Light Bakary MSU Graphics Group Student's Diploma Project Treefonov Andrey [GitHub] [LinkedIn] Project Goal The goal of the project is to imple
Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].
Time2box Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].
This is a tensorflow-based rotation detection benchmark, also called AlphaRotate.
AlphaRotate: A Rotation Detection Benchmark using TensorFlow Abstract AlphaRotate is maintained by Xue Yang with Shanghai Jiao Tong University supervi
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar
A python script that changes your desktop background based on current weather and time of the day.
Desktop background wallpaper, based on current weather and time A python script that changes your computer's desktop background based on current weath
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.
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
Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019) This repository contains python (3.5.2) implementation of
Short and long time series classification using convolutional neural networks
time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
sktime companion package for deep learning based on TensorFlow
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
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D