1508 Open source projects that are alternatives of or similar to Time Attention

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.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

PyTorch tutorial for learners

The Official Deep Learning Framework for Route-based Place Recognition

CNN, LSTM, NBOW, fasttext 中文文本分类

Keras tutorial for beginners (using TF backend)

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

中文聊天机器人，基于10万组对白训练而成，采用注意力机制，对一般问题都会生成一个有意义的答复。已上传模型，可直接运行，跑不起来直播吃键盘。

Enhanced BiLSTM Inference Model for Natural Language Inference

List of papers, code and experiments using deep learning for time series forecasting

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

My Attempt(s) In The World Of ML/DL....

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

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.

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

基於關聯式新聞提取方法之雙階段注意力機制模型用於股票預測

Tensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

A Natural Language Toolkit for Indian Languages

Lightweight C++11 library for building deep recurrent neural networks

Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs

Hybrid Code Networks https://arxiv.org/abs/1702.03274

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.

CPU and GPU implementations of some 2D RNN layers

Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework

分别使用rnn/cnn/rcnn来实现根据患者描述，进行疾病诊断

rnn trained on r/totallynotrobots 🤖

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

Image captioning using attention models

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

A collection of UNet and hybrid architectures in PyTorch for 2D and 3D Biomedical Image segmentation

CRNN with attention to do OCR,add Chinese recognition

A stock trading bot that uses machine learning to make price predictions.

中文古诗自动作诗机器人，屌炸天，基于tensorflow1.10 api，正在积极维护升级中，快star，保持更新！

BasicOCR是一个致力于解决自然场景文字识别算法研究的项目。该项目由长城数字大数据应用技术研究院佟派AI团队发起和维护。

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)

Easy-to-use Deep LSTM Neural Network to generate song sounds like containing improvisation.

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

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

RMDL: Random Multimodel Deep Learning for Classification

🌊 Numerically solving and backpropagating through the wave equation

Named Entity Recognition using multilayered bidirectional LSTM

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

Recurrent (conditional) generative adversarial networks for generating real-valued time series data.

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.

Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset.

Stock Price Prediction using Machine Learning Techniques

Implementation of papers for text classification task on DBpedia

RNN based Time-series Anomaly detector model implemented in Pytorch.

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

Tensorflow implementation of attention mechanism for text classification tasks.

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.