1133 Open source projects that are alternatives of or similar to dts

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

News summarization using sequence to sequence model with attention in TensorFlow.

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

Using LSTM network for time series forecasting

Anomaly detection for temporal data using LSTMs

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

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.

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

Application of machine learning to the Coinbase (GDAX) orderbook

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

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

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

Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)

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

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

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

Machine Learning on Sequential Data Using a Recurrent Weighted Average

Feeding images of time series to Conv Nets! (Tensorflow + Keras)

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

GANs for time series generation in pytorch

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

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.

1st place solution

TensorFlow Implementation of Twitter Chatbot

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

Deep-Learning Model Exploration and Development for NLP

Machine learning models for time series analysis

Renewcast: Forecasting Renewable Electricity Generation in EU Countries.

A collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter

Recurrent Additive Networks for Tensorflow

Example of order book modeling.

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.

Deep Learning

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

Annotation of ECG signals using deep learning, tensorflow’ Keras

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.

Library of autoencoders for sequential data

Probabilistic time series modeling in Python

Keras implementation of Legendre Memory Units

bitcoin prediction algorithms

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

Official code for UnICORNN (ICML 2021)

COVID-19 spread shiny dashboard with a forecasting model, countries' trajectories graphs, and cluster analysis tools

LSTM, GRU cell implementation from scratch in tensorflow

Gathers Tensorflow deep learning models.

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

A simple open domain generative based chatbot based on Recurrent Neural Networks

Keras and PyTorch implementations of the MaLSTM model for computing Semantic Similarity.

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

Fiction generator with Tensorflow. 模仿王小波的风格的小说生成器

Resources for working with time series and sequence data

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.