434 Open source projects that are alternatives of or similar to Seq2seq Pytorch

1st place solution

Natural Language Processing with TensorFlow, published by Packt

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

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

Sequence to sequence learning with MXNET

Multiple implementations for abstractive text summurization , using google colab

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

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

Chinese Poetry Generation

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。

텐서플로2와 머신러닝으로 시작하는 자연어처리 (로지스틱회귀부터 BERT와 GPT3까지) 실습자료

Code lab for deep learning. Including rnn,seq2seq,word2vec,cross entropy,bidirectional rnn,convolution operation,pooling operation,InceptionV3,transfer learning.

Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle.

Implementing Recurrent Neural Network from Scratch

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

Keras tutorial for beginners (using TF backend)

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

A top-down, practical guide to learn AI, Deep learning and Machine Learning.

sliced-rnn

Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes

Image to LaTeX (Seq2seq + Attention with Beam Search) - Tensorflow

Char-RNN implemented using TensorFlow.

CNN-RNN中文文本分类，基于TensorFlow

Pytorch seq2seq chatbot

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

深度学习入门教程, 优秀文章, Deep Learning Tutorial

[unmaintained]

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！

Implementation of State-of-the-art Text Classification Models in Pytorch

此项目致力于构建一套最基础，最精简，可维护的react-native项目，支持ios，android 🌹

RMDL: Random Multimodel Deep Learning for Classification

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

A wrapper around tensor2tensor to flexibly train, interact, and generate data for neural chatbots.

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

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.

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

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

Deep Recurrent Neural Networks for Source Separation

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

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。

Minimalist NMT for educational purposes

PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning https://arxiv.org/abs/1611.09940

WTTE-RNN a framework for churn and time to event prediction

Generating bash command from natural language https://arxiv.org/abs/1802.08979

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

This repository contains a new generative model of chatbot based on seq2seq modeling.

A Tensorflow Implementation of R-net: Machine reading comprehension with self matching networks

Tensorflow seq2seq Implementation of Text Summarization.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

Repository for the tutorial on Sequence-Aware Recommender Systems held at TheWebConf 2019 and ACM RecSys 2018

基于seq2seq模型的简单对话系统的tf实现，具有embedding、attention、beam_search等功能，数据集是Cornell Movie Dialogs

End-to-end ASR/LM implementation with PyTorch

Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

A tensorflow implementation of Fairseq Convolutional Sequence to Sequence Learning(Gehring et al. 2017)

A simple, minimal wrapper for tensorflow's seq2seq module, for experimenting with datasets rapidly

Automatically generate headlines to short articles

Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com

Pointer-generator reinforced seq2seq summarization in PyTorch

seq2seq中文聊天机器人

Sequence-to-Sequence Framework in PyTorch