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

Anomaly detection for temporal data using LSTMs

🥕 Evolutionary Neural Networks in JavaScript

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

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

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

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

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

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

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)

Image Captioning: Implementing the Neural Image Caption Generator with python

A Natural Language Toolkit for Indian Languages

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

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

A Python package for gender classification.

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

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

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

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

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

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

Named Entity Recognition with RNN, implemented by Chainer

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

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

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

Neural machine translator for English2German translation.

The Official Deep Learning Framework for Route-based Place Recognition

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

Anomaly detection implemented in Keras

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.

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Plain Stock Close-Price Prediction via Graves LSTM RNNs

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

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

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

Using LSTM network for time series forecasting

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).

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

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

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

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Named Entity Recognition using multilayered bidirectional LSTM

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

Application of machine learning to the Coinbase (GDAX) orderbook

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

PyTorch tutorial for learners

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

The first public PyTorch implementation of Attentive Recurrent Comparators

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Implementation of "Generating Sequences With Recurrent Neural Networks" https://arxiv.org/abs/1308.0850

Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

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

A (CNN+)RNN(LSTM/BiLSTM)+CRF model for sequence labelling.😏

PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

深度学习与PyTorch入门实战视频教程 配套源代码和PPT

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

TensorFlow template application for deep learning

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

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond