66 Repositories
Python rnn-gru Libraries
Repository for RNNs using TensorFlow and Keras - LSTM and GRU Implementation from Scratch - Simple Classification and Regression Problem using RNNs
RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for
Curso práctico: NLP de cero a cien 🤗
Curso Práctico: NLP de cero a cien Comprende todos los conceptos y arquitecturas clave del estado del arte del NLP y aplícalos a casos prácticos utili
An excellent hash algorithm combining classical sponge structure and RNN.
SHA-RNN Recurrent Neural Network with Chaotic System for Hash Functions Anonymous Authors [摘要] 在这次作业中我们提出了一种新的 Hash Function —— SHA-RNN。其以海绵结构为基础,融合了混
Process text, including tokenizing and representing sentences as vectors and Applying some concepts like RNN, LSTM and GRU to create a classifier can detect the language in which a sentence is written from among 17 languages.
Language Identifier What is this ? The goal of this project is to create a model that is able to predict a given sentence language through text proces
TimeSHAP explains Recurrent Neural Network predictions.
TimeSHAP TimeSHAP is a model-agnostic, recurrent explainer that builds upon KernelSHAP and extends it to the sequential domain. TimeSHAP computes even
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
Static Features Classifier - A static features classifier for Point-Could clusters using an Attention-RNN model
Static Features Classifier This is a static features classifier for Point-Could
Animal Sound Classification (Cats Vrs Dogs Audio Sentiment Classification)
this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.
Film review classification
Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З
auto_code_complete is a auto word-completetion program which allows you to customize it on your need
auto_code_complete v1.3 purpose and usage auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the m
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete
PyTorch GPU implementation of the ES-RNN model for time series forecasting
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm A GPU-enabled version of the hybrid ES-RNN model by Slawek et al that won the M4 time-series
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
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
In this project we can see how we can generate automatic music using character RNN.
Automatic Music Genaration Table of Contents Project Description Approach towards the problem Limitations Libraries Used Summary Applications Referenc
Pytorch implementation of the popular Improv RNN model originally proposed by the Magenta team.
Pytorch Implementation of Improv RNN Overview This code is a pytorch implementation of the popular Improv RNN model originally implemented by the Mage
Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy
lbs-data Motivation Location data is collected from the public by private firms via mobile devices. Can this data also be used to serve the public goo
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter
Predictive Maintenance LSTM
Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR
HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H
Memory efficient transducer loss computation
Introduction This project implements the optimization techniques proposed in Improving RNN Transducer Modeling for End-to-End Speech Recognition to re
Official repository for "Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring".
RNN-MBP Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring (AAAI-2022) by Chao Zhu, Hang Dong, Jinshan Pan
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon
Generative Handwriting using LSTM Mixture Density Network with TensorFlow
Generative Handwriting Demo using TensorFlow An attempt to implement the random handwriting generation portion of Alex Graves' paper. See my blog post
Chatbot in 200 lines of code using TensorLayer
Seq2Seq Chatbot This is a 200 lines implementation of Twitter/Cornell-Movie Chatbot, please read the following references before you read the code: Pr
Hierarchical Attentive Recurrent Tracking
Hierarchical Attentive Recurrent Tracking This is an official Tensorflow implementation of single object tracking in videos by using hierarchical atte
A Tensorfflow implementation of Attend, Infer, Repeat
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models This is an unofficial Tensorflow implementation of Attend, Infear, Repeat (AIR)
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
Conformal time-series forecasting Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021. If you use our code in yo
Emotion classification of online comments based on RNN
emotion_classification Emotion classification of online comments based on RNN, the accuracy of the model in the test set reaches 99% data: Large Movie
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
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
RNN Predict Street Commercial Vitality
RNN-for-Predicting-Street-Vitality Code and dataset for Predicting the Vitality of Stores along the Street based on Business Type Sequence via Recurre
Implementation of C-RNN-GAN.
Implementation of C-RNN-GAN. Publication: Title: C-RNN-GAN: Continuous recurrent neural networks with adversarial training Information: http://mogren.
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
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
This repository contains the reference implementation for our proposed Convolutional CRFs.
ConvCRF This repository contains the reference implementation for our proposed Convolutional CRFs in PyTorch (Tensorflow planned). The two main entry-
Using a Seq2Seq RNN architecture via TensorFlow to predict future Bitcoin prices
Recurrent Bitcoin Network A Data Science Thesis Project About This repository contains the source code for implementing Bitcoin price prediciton using
a reccurrent neural netowrk that when trained on a peice of text and fed a starting prompt will write its on 250 character text using LSTM layers
RNN-Playwrite a reccurrent neural netowrk that when trained on a peice of text and fed a starting prompt will write its on 250 character text using LS
keyframes-CNN-RNN(action recognition)
keyframes-CNN-RNN(action recognition) Environment: python=3.7 pytorch=1.2 Datasets: Following the format of UCF101 action recognition. Run steps: Mo
Machine Translation Implement By Bi-GRU And Transformer
Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
GCN_LogsigRNN This repository holds the codebase for the paper: Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
Implements Stacked-RNN in numpy and torch with manual forward and backward functions
Recurrent Neural Networks Implements simple recurrent network and a stacked recurrent network in numpy and torch respectively. Both flavours implement
Website which uses Deep Learning to generate horror stories.
Creepypasta - Text Generator Website which uses Deep Learning to generate horror stories. View Demo · View Website Repo · Report Bug · Request Feature
LSTMs (Long Short Term Memory) RNN for prediction of price trends
Price Prediction with Recurrent Neural Networks LSTMs BTC-USD price prediction with deep learning algorithm. Artificial Neural Networks specifically L
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition Identify the emotion of multiple speakers in a Audio Segment Report Bug · Request Feature Try the Demo Here Table
Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"
RNN-for-Joint-NLU Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
DeepNLP-models-Pytorch Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning) This is not for Pytorch be
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
Sequence to Sequence Models with PyTorch
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
基于GRU网络的句子判断程序/A program based on GRU network for judging sentences
SentencesJudger SentencesJudger 是一个基于GRU神经网络的句子判断程序,基本的功能是判断文章中的某一句话是否为一个优美的句子。 English 如何使用SentencesJudger 确认Python运行环境 安装pyTorch与LTP python3 -m pip
A pytorch implementation of Pytorch-Sketch-RNN
Pytorch-Sketch-RNN A pytorch implementation of https://arxiv.org/abs/1704.03477 In order to draw other things than cats, you will find more drawing da
Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch
Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
This is the official repository of my book "Deep Learning with PyTorch Step-by-Step". Here you will find one Jupyter notebook for every chapter in the book.
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s
Algorithmic Trading using RNN
Deep-Trading This an implementation adapted from Rachnog Neural networks for algorithmic trading. Part One — Simple time series forecasting and this c
Predict stock movement with Machine Learning and Deep Learning algorithms
Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th
Handwriting Recognition System based on a deep Convolutional Recurrent Neural Network architecture
Handwriting Recognition System This repository is the Tensorflow implementation of the Handwriting Recognition System described in Handwriting Recogni
📝 Wrapper library for text generation / language models at char and word level with RNN in TensorFlow
tensorlm Generate Shakespeare poems with 4 lines of code. Installation tensorlm is written in / for Python 3.4+ and TensorFlow 1.1+ pip3 install tenso