584 Open source projects that are alternatives of or similar to Char Rnn Keras

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

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

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

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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

A Natural Language Toolkit for Indian Languages

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

Neural machine translator for English2German translation.

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

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).

Using LSTM network for time series forecasting

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

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

Named Entity Recognition with RNN, implemented by Chainer

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

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

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

PyTorch tutorial for learners

Image Captioning: Implementing the Neural Image Caption Generator with python

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

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.

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

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

🥕 Evolutionary Neural Networks in JavaScript

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

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

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Anomaly detection for temporal data using LSTMs

A Keras library for multi-step time-series forecasting.

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.

The Official Deep Learning Framework for Route-based Place Recognition

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

A Python package for gender classification.

Application of machine learning to the Coinbase (GDAX) orderbook

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

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

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

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

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Keras implementation of Legendre Memory Units

Plain Stock Close-Price Prediction via Graves LSTM RNNs

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

Anomaly detection implemented in Keras

Named Entity Recognition using multilayered bidirectional LSTM

Self-contained Machine Learning and Natural Language Processing library in Go

THEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.

speaker diarization system using an LSTM

PyTorch Implementation of the RDPG (Recurrent Deterministic Policy Gradient)

Official PyTorch implementation of paper "A Hybrid Compact Neural Architecture for Visual Place Recognition" by M. Chancán (RA-L & ICRA 2020) https://doi.org/10.1109/LRA.2020.2967324

QA - Answer Selection (Rank candidate answers for a given question)

An implementation of zoneout regularizer on LSTM-RNN by Tensorflow

Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis

Multitask learning: protein secondary structure prediction, b-values prediction and solvent-accessibility prediction

Recurrent Neural Network using randomized SMILES strings to generate molecules

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

Design and build a chatbot using data from the Cornell Movie Dialogues corpus, using Keras

Convert TensorFlow models to ONNX