860 Open source projects that are alternatives of or similar to Deep News Summarization

模仿莎士比亚创作戏剧！屌炸天的是还能创作金庸武侠小说！快star，保持更新！！

Neural network that solves math equations on the character level

Sorting numbers with pointer networks

Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587

Anomaly detection implemented in Keras

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

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.

🥕 Evolutionary Neural Networks in JavaScript

Bangla Machine Translator

Tensorflow seq2seq Implementation of Text Summarization.

TensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts

PyTorch tutorial for learners

Chinese Poetry Generation

Application of machine learning to the Coinbase (GDAX) orderbook

Implementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.

A Python package for gender classification.

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

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 analyzing using Recurrent Neural Networks (RNN) based on Keras

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Some of the ML and DL related reading materials, research papers that I've read

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

Neural network models for joint POS tagging and dependency parsing (CoNLL 2017-2018)

Lyrics Generator aka Character-level Language Modeling with Multi-layer LSTM Recurrent Neural Network

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

Tensorflow Implementation of "Recurrent Convolutional Neural Network for Text Classification" (AAAI 2015)

convolutional lstm implementation in pytorch

semantic analysis using word2vector, doc2vector,lstm and other method. mainly for text similarity analysis.

An iOS application of Tensorflow Object Detection with different models: SSD with Mobilenet, SSD with InceptionV2, Faster-RCNN-resnet101

ECG classification programs based on ML/DL methods

Library of autoencoders for sequential data

iPython notebook and Android app that shows how to build LSTM model in TensorFlow and deploy it on Android

基于RNN生成古诗

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

1st place solution

TensorFlow implementation of Conversation Models

Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs

Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)

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

keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS

datagrand 2019 information extraction competition rank9

Automatic Number (License) Plate Recognition using Tensorflow Object Detection API

Demo code of the paper: "Deep Image Harmonization", Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu and M.-H. Yang, CVPR 2017

It is a question-generator model. It takes text and an answer as input and outputs a question.

SRU is a recurrent unit that can run over 10 times faster than cuDNN LSTM, without loss of accuracy tested on many tasks.

How to build RNNs and LSTMs from scratch with NumPy.

🔥🔥🔥自定义Android相机(仿抖音 TikTok)，其中功能包括视频人脸识别贴纸，美颜，分段录制，视频裁剪，视频帧处理，获取视频关键帧，视频旋转，添加滤镜，添加水印，合成Gif到视频，文字转视频，图片转视频，音视频合成，音频变声处理，SoundTouch，Fmod音频处理。 Android camera(imitation Tik Tok), which includes video editor,audio editor,video face recognition stickers, segment recording,video cropping, video frame processing, get the first video frame, key frame, v…

ConText v4: Neural networks for text categorization

A R/Shiny app for interactive RNN tensorflow models

Pointer Networks Implementation in Keras

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

A Bitcoin trade robot based on Tensorflow LSTM model.Just for fun.

A Collection of resources I have found useful on my journey finding my way through the world of Deep Learning.

Penetration Testing and Hacking CTF's Swiss Army Knife with: Reverse Shell Handling - Encoding/Decoding - Encryption/Decryption - Cracking Hashes / Hashing

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

Neural word segmentation with rich pretraining, code for ACL 2017 paper

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0