398 Open source projects that are alternatives of or similar to Pointer Networks

Neural machine translator for English2German translation.

Use unsupervised and supervised learning to predict stocks

PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

Time series based anomaly detector

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

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

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

主流ocr算法研究实验性的项目，目前实现了CNN+BLSTM+CTC架构

Sarcasm detection on tweets using neural network

CNN, LSTM, NBOW, fasttext 中文文本分类

A Python package for gender classification.

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

Context-Dependent Sentiment Analysis in User-Generated Videos

The deeplearning algorithms implemented by tensorflow

copper price(time series) prediction using bpnn and lstm

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

Word Embedding + LSTM + FC

Tensorflow Implementation of GAN modeling for sequential data

Keras implementation of video classifier

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

Using Machine Learning to predict the type of exercise from movement data

PyTorch tutorial for learners

Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.

Application of machine learning to the Coinbase (GDAX) orderbook

All my experiments with AI and ML

LSTM and CNN sentiment analysis

Implementation of the paper - Generative Recurrent Networks for De Novo Drug Design.

A fast LSTM Language Model for large vocabulary language like Japanese and Chinese

document classification using LSTM + self attention

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

RNN and general weights, gradients, & activations visualization in Keras & TensorFlow

A PyTorch Tutorials of Sentiment Analysis Classification (RNN, LSTM, Bi-LSTM, LSTM+Attention, CNN)

Models for predicting emotions from English tweets.

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

I used in this project a reccurent neural network to generate c code based on a dataset of c files from the linux repository.

This repository contains PyTorch implementation for the baseline models from the paper Utterance-level Dialogue Understanding: An Empirical Study

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

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

Time series prediction with Sequential Model and LSTM units

NN based lossless compression

Annotation of ECG signals using deep learning, tensorflow’ Keras

An extension on the Hierachical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion, our implementation is in Tensorflow and uses an attention mechanism.

A Tensorflow based implicit recommender system

Bert-classification and bert-dssm implementation with keras.

LSTM and GRU in PyTorch

Ideal Ratio Mask (IRM) Estimation based Speech Enhancement using LSTM

Char-level RNN LSTM text generator📄.

Sign Language Recognition for Deaf People

This package contains an OCR engine - libtesseract and a command line program - tesseract. Tesseract 4 adds a new neural net (LSTM) based OCR engine which is focused on line recognition, but also still supports the legacy Tesseract OCR engine of Tesseract 3 which works by recognizing character patterns. Compatibility with Tesseract 3 is enabled by using the Legacy OCR Engine mode (--oem 0). It also needs traineddata files which support the legacy engine, for example those from the tessdata repository.

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

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

Anomaly detection for streaming data using autoencoders

GANs for time series generation in pytorch

Machine learning, in numpy

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