Tensorflow Lstm SinTensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction
Stars: ✭ 52 (+173.68%)
Deep Learning Time SeriesList of papers, code and experiments using deep learning for time series forecasting
Stars: ✭ 796 (+4089.47%)
Linear Attention Recurrent Neural NetworkA 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)
Stars: ✭ 119 (+526.32%)
Ner LstmNamed Entity Recognition using multilayered bidirectional LSTM
Stars: ✭ 532 (+2700%)
SpeakerDiarization RNN CNN LSTMSpeaker 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).
Stars: ✭ 56 (+194.74%)
SangitaA Natural Language Toolkit for Indian Languages
Stars: ✭ 43 (+126.32%)
Language TranslationNeural machine translator for English2German translation.
Stars: ✭ 82 (+331.58%)
Multitask sentiment analysisMultitask 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
Stars: ✭ 93 (+389.47%)
datastories-semeval2017-task6Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
Stars: ✭ 20 (+5.26%)
CS231nPyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
Stars: ✭ 47 (+147.37%)
Carrot🥕 Evolutionary Neural Networks in JavaScript
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Char Rnn KerasTensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts
Stars: ✭ 40 (+110.53%)
sgrnnTensorflow implementation of Synthetic Gradient for RNN (LSTM)
Stars: ✭ 40 (+110.53%)
Lstm Ctc Ocrusing rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc
Stars: ✭ 70 (+268.42%)
Rnn Text Classification TfTensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification
Stars: ✭ 114 (+500%)
Image CaptioningImage Captioning: Implementing the Neural Image Caption Generator with python
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Deep News SummarizationNews summarization using sequence to sequence model with attention in TensorFlow.
Stars: ✭ 167 (+778.95%)
Pytorch Kaldipytorch-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.
Stars: ✭ 2,097 (+10936.84%)
Rnn ctcRecurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
Stars: ✭ 220 (+1057.89%)
dtsA Keras library for multi-step time-series forecasting.
Stars: ✭ 130 (+584.21%)
tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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Document Classifier LstmA bidirectional LSTM with attention for multiclass/multilabel text classification.
Stars: ✭ 136 (+615.79%)
RnnsharpRNNSharp 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.
Stars: ✭ 277 (+1357.89%)
Machine Learning Curriculum💻 Make machines learn so that you don't have to struggle to program them; The ultimate list
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Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
Stars: ✭ 3,209 (+16789.47%)
LstmvisVisualization Toolbox for Long Short Term Memory networks (LSTMs)
Stars: ✭ 959 (+4947.37%)
DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
Stars: ✭ 49 (+157.89%)
ChicksexerA Python package for gender classification.
Stars: ✭ 64 (+236.84%)
Gdax Orderbook MlApplication of machine learning to the Coinbase (GDAX) orderbook
Stars: ✭ 60 (+215.79%)
Ai Reading MaterialsSome of the ML and DL related reading materials, research papers that I've read
Stars: ✭ 79 (+315.79%)
Pytorch Pos TaggingA tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.
Stars: ✭ 96 (+405.26%)
Image Caption GeneratorA neural network to generate captions for an image using CNN and RNN with BEAM Search.
Stars: ✭ 126 (+563.16%)
Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
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Keras LmuKeras implementation of Legendre Memory Units
Stars: ✭ 160 (+742.11%)
Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
Stars: ✭ 146 (+668.42%)
StockpredictionPlain Stock Close-Price Prediction via Graves LSTM RNNs
Stars: ✭ 134 (+605.26%)
sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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Lstm Human Activity RecognitionHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
Stars: ✭ 2,943 (+15389.47%)
Text ClassificationImplementation of papers for text classification task on DBpedia
Stars: ✭ 682 (+3489.47%)
Test TubePython library to easily log experiments and parallelize hyperparameter search for neural networks
Stars: ✭ 663 (+3389.47%)
CtcdecoderConnectionist Temporal Classification (CTC) decoding algorithms: best path, prefix search, beam search and token passing. Implemented in Python.
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ChainerA flexible framework of neural networks for deep learning
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Qa使用深度学习算法实现的中文问答系统
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